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Live Nation Entertainment (LYV) Stock Stays Hard To Read After Its 93% Run
Live Nation Entertainment has seen its share price advance strongly over the past few years, which naturally puts the focus on whether the current US$168.77 level is supported by what the business can generate in cash. With the stock giving back some ground in recent weeks, the question now is how that recent share move lines up against the value implied by its cash flows. Over the past 3 years the stock has returned 92.9%, which raises the issue of whether the market is now asking investors...
NVIDIA Raises Shield TV Pro Price to $299, Discontinues Standard Shield TV
NVIDIA has raised the price of the Shield TV Pro from $199.99 to $299.99, effective October 2. The streaming box launched in October 2019 at $199.99 and held that price for almost seven years. Earlier this year, NVIDIA promised to keep updating the Shield TV, with hardware engineering SVP Andrew...
Your gut may be making a molecule that raises Alzheimer’s risk
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U.S.-Russia Talks on Ukraine Now Involve an Oil Deal Tied to Trump Allies
President Vladimir V. Putin brought up a sale of Russian energy assets with President Trump’s envoys, Jared Kushner and Steve Witkoff, pushing a deal that raises new questions about conflicts of interest.
J.J. McCarthy feels 'blessed' after Giants trade, loves the Harbaughs
J.J. McCarthy calls his Vikings-to-New York Giants trade a shock and an opportunity, says he feels blessed, and praises the Harbaughs.
A system under strain: Deadly attack raises questions about mental health beds
Second-degree murder, attempted murder, and assault- crimes that happened in three counties over the course of six weeks.
Pacers Coach Rick Carlisle Strongly Praises Newcomer Kelly Oubre Jr.
Indiana Pacers head coach Rick Carlisle praised new small forward Kelly Oubre Jr.
Bishop’s computer science chair says AI is eliminating ‘grunt work’ and reshaping digital jobs
Dr. Russell Butler, chair of Bishop’s University’s Department of Computer Science, says artificial intelligence is increasingly taking over routine digital “grunt work,” changing the skills students and workers may need in the years ahead. Photo courtesy of Bishop’s University. Click here to read our platform! Get local news like this every morning. Subscribe free below. Subscribe Pulse Newsroom Artificial intelligence is already taking over some of the routine digital work once performed by entry-level employees, according to Bishop’s University Computer Science chair Dr. Russell Butler — a shift he believes will make expertise, judgement and the ability to evaluate AI-generated work increasingly important. Butler described the change as automation reaching what he calls the “bottom of the cognitive pyramid” during an interview with The Pulse about AI, university education and the future of digital work. His argument is not that humans are disappearing from the workplace. Instead, he sees their role changing as AI becomes capable of handling more of the repetitive tasks involved in computer-based work. “Everything’s converging on just AI basically doing all the grunt work,” Butler said. The bottom of the cognitive pyramid Butler is from Lennoxville, completed his undergraduate studies at Bishop’s and later earned his PhD at the Université de Sherbrooke. He joined Bishop’s in 2019 and now chairs its Department of Computer Science. He uses AI in research, teaching and other creative work, and said the technology is increasingly capable of handling routine digital tasks that once required substantial human time. “You’ve got the grunt work, like moving things around in Excel, doing basic programming tasks,” Butler said. “That’s like the bottom grunt work that the entry-level worker would have done two or three years ago.” Butler went further, saying in his view that much of this type of work has already been absorbed by AI tools. He connected that change to a shift he sees taking place in computer science, where entry-level roles have declined while experienced workers can use AI to increase what they can produce. “A senior developer now has access to essentially an unlimited amount of junior developers on demand,” Butler said. He was describing AI systems metaphorically, not literal employees. His point was that one experienced developer can now ask AI tools to produce code or other technical work that might previously have been assigned to more junior workers. That raises a broader question for universities and employers. If some of the simpler work traditionally given to newcomers can now be done by machines, how do people gain the experience needed to become senior workers themselves? Students doing work that once required years of programming Butler said he is already seeing the change inside his classroom. He created a Bishop’s course called CS208, Coding in Plain English, to show students — including those without traditional programming backgrounds — what they can accomplish using AI. Some come from disciplines such as psychology or neuroscience with no previous programming experience. “What I’m finding is that students who have zero programming experience, they come in from another discipline like psychology or neuroscience or something, they are now able to get up and running with real data sets,” Butler said. Butler’s own doctoral work involved neuroimaging, and he said he has assigned students work he considers comparable to the kinds of analysis he performed during his PhD. He described giving students a real dataset, an expected result and instructions to use AI to complete the analysis. Butler said those students have been able to carry out work at a level he associates with tasks he once performed after years of programming experience. That does not mean a student using AI instantly acquires the same knowledge as an experienced computer scientist. But Butler sees it as evidence that AI can dramatically lower the technical barrier between having a problem to solve and producing a working result. The role of the person using the system then changes. They need to know what to ask for, understand enough about the subject to judge the answer and take responsibility for what is ultimately produced. What about AI hallucinations? One persistent concern surrounding generative AI is hallucination — when a system produces information that sounds convincing but is false or unsupported. Butler said that problem has improved substantially in newer systems and is not as severe as it was with earlier models. He pointed in particular to newer AI systems’ ability to search the web, consult scientific databases and return source links rather than simply generating a citation from their internal model. Butler nevertheless said users should verify what AI produces. “You should verify,” he said while discussing citations generated with AI. His position is that hallucinations have become less common in the systems he uses, not that incorrect AI output is impossible. Human checking remains part of the process. Hours of work compressed Butler offered another example from his administrative work at Bishop’s. The university has been comparing CEGEP courses with first-year Bishop’s courses to determine where students may qualify for advanced standing. Traditionally, Butler said, that means reviewing two sets of course descriptions and manually matching one institution’s courses with another’s. As department chair, that could require hours of reading and comparison. He said AI can now be given both sets of material and asked to generate an initial mapping automatically. “It saves me hours and hours of work,” Butler said. Butler said the AI-generated mapping can also produce a better result than he would produce himself. He sees similar opportunities in businesses. A company may receive specifications, drawings, emails or other digital material from customers and then have employees convert that information into an internal format before anything can be manufactured or delivered. AI can increasingly perform parts of that intermediate processing. In Butler’s view, the employee does not necessarily disappear. Instead, the job becomes more about checking the result. “The human is still there,” he said. Judgement could become more valuable That change is central to Butler’s view of where digital work may be headed. If AI can produce a first draft, write basic code, compare documents or process large amounts of information, he argues that knowledge and judgement become increasingly important. “The real scarce resource going forward is going to be domain knowledge, expertise, and… credentials, authority, the ability to work with other people,” Butler said. He is therefore encouraging students not only to learn AI tools but also to broaden their education. He mentioned acting, fine art and photography as examples of courses that can help develop what he described as taste and intuition — the ability to recognize what is good, what is not and what should be changed. “And that’s the skill that they need now because the grunt work has been automated and now it’s about evaluating what the AI produces and telling it how to improve or expand the output,” Butler said. That does not remove the need for technical knowledge. Butler’s argument is that the emphasis may shift away from manually completing every step of a task and toward directing, checking and improving work produced with AI assistance. He also stressed that humans remain responsible for final decisions. “At the end of the day, the human has to make the final call,” Butler said, pointing to the question of accountability. Physical work may be different Butler draws a distinction between digital work and jobs requiring people to manipulate the physical world. He expects AI to continue advancing quickly in tasks performed almost entirely on computers. He is more cautious about claims that humanoid robots will soon be able to replace workers such as plumbers or electricians. Butler said those trades would not be replaced “anytime soon” in his view and described some current robotics demonstrations as overhyped. He described the situation as counterintuitive. “It’s almost like we solved the highest level first,” he said, contrasting advances in digital AI with the harder problem of building robots capable of operating reliably in the physical world. Butler’s argument is that some digital occupations could face automation sooner than trades requiring complex physical work. The wider AI shift in the Townships Butler’s comments come as local institutions are increasingly grappling with how AI should be used. The federal government recently announced up to $162 million over five years for 10,000 AI-related placements through Mitacs. The Université de Sherbrooke told The Pulse that the number of its collaborative research and innovation projects supported through Mitacs has approximately doubled since 2018-19, while the number of placements has approximately tripled. UdeS also said it already has projects involving both AI adoption and the application of AI to other fields. At Bishop’s, Butler said part of his role involves building the Computer Science department’s local presence, connecting students with regional partners and strengthening relationships with the Sherbrooke technology ecosystem. Those developments put universities in a difficult position. They have to prepare students to use the tools employers increasingly have available while also making sure graduates understand enough to recognize when those tools are wrong, incomplete or being applied to the wrong problem. The risk of losing human skills Butler does not see AI as risk-free. Later in the interview, he raised a separate concern: as AI becomes better at reading, writing, programming and other cognitive tasks, people could lose some of the underlying skills that historically helped produce new ideas. “The other danger is that we’re going to lose the human skills,” Butler said. He specifically mentioned reading and writing and argued that people could lose some of the lower-level understanding that contributes to breakthroughs. Butler said AI systems are based on existing human knowledge and argued that they become much more powerful when paired with a capable person. That tension runs through his view of the technology. AI can remove hours of routine work. It can allow beginners to perform tasks that once required substantial technical training. It can give experienced workers significant leverage. But the more capable the technology becomes, the more important it may be for people to develop the judgement needed to decide what should be done in the first place. For Butler, that is where education may have to change. Students still need to understand their field. They still need to know when something is wrong. And they still need to be able to make the final decision. But if AI increasingly handles the bottom of the cognitive pyramid, the value of a worker may depend less on how quickly they can perform the grunt work and more on whether they understand what the work is supposed to accomplish. Don’t miss the next story that affects your community. Join thousands of readers getting The Pulse every morning—plus breaking news alerts when it matters most. If you value this kind of local journalism, consider supporting it. Subscribe, share and like! Subscribe Share
Junior Achievement honors Eastern Iowa business leaders, raises more than $167,000
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Good science requires much more than evidence
Empiricists believe that scientific theories are true only if they make correct empirical predictions: if we can't verify these predictions, then there is no reason to expect that they tell us anything about reality. However, Professor of Philosophy at King's College David Kyle Johnson argues that this is mistaken. In response to Bas van Fraassen, who has written on this subject for the IAI, he argues that we have many reasons for believing a theory to be true, such as it being parsimonious and having large scope — qualities which have been used throughout the history of science as criteria for judging theories. In 2024, Princeton philosopher Bas van Fraassen wrote a short article for IAI News entitled “Science Does not Describe Reality: The Limits and Benefits of Explanation.” At the time, I was working on two projects (a science book and a Great Course) that, when completed, would (among other things) defend science’s ability to describe reality. I wanted to write a response to van Fraassen, but the projects demanded too much of my attention. But now that those projects are complete, I am in a position to explain the objections to van Fraassen’s thesis. Summarizing van Fraassen’s argumentIn a nutshell, his argument is this: What scientists do is make predictions based on theories and then invite others to test to see whether those predictions are borne out. “If theory T is right, result R should happen in experimental condition C.” Many think that running an experiment that shows that R happens in condition C is proof that theory T is true (and should be believed). But, van Fraassen argues, that R happened in condition C is only a reason to think that R happens in condition C. That’s the only observable, or empirical, result we can actually see, so that is all that we are really justified in believing. (The underlying theory that made that prediction still may or may not be true.) That is why he calls those who accept his position “empiricists.”Before I explain what is wrong with this position, let me explain what it gets right. What van Fraassen Gets RightFirst, a theory correctly predicting the results of an experiment is not, strictly speaking, “proof” that the theory is correct. The basic line of reasoning is this:If the theory T is true, result R should happen. Result R did happen. Thus, theory T is true.In other words:“If T then R. R. Thus, T.”This is a deductively invalid, fallacious mode of reasoning, called “affirming the consequent.” Those premises do not guarantee that the conclusion follows. “If I am in Pennsylvania, then I am in the USA. I am in the USA. Thus, I am in Pennsylvania.” Clearly that argument doesn’t guarantee its conclusion; neither does the above argument.However, science is not a deductive method of reasoning; it is an inductive one. And inductive arguments merely try to raise the probability of their conclusion, not “prove” them for certain. Thus, the fact that an experimental result doesn’t prove a theory is true is irrelevant; it’s not supposed to. That is not what scientific reasoning is about.___If the hypothesis that something exists clearly provides the best explanation for what we can observe, then the belief that it exists is what is rational.___Second, it’s also true that a single experimental result doesn’t provide enough justification to believe that a theory is true. Scientists do not come to a consensus about whether a theory is true by looking at a single experiment; they look at all the evidence to determine where the preponderance of evidence points. The mere fact that I am in the USA raises the probability that I am in Pennsylvania, but not nearly enough to conclude that I am in Pennsylvania. However, if I am also regularly encountering people wearing Eagles and Phillies hats and seeing advertisements for Founding Father tours, I probably am. In the same way, a theory successfully predicting the outcome of one experiment is not enough to conclude that it is true; but if a theory makes a wide variety of predictions that are all vindicated by multiple experiments, performed by many different groups and people, all actively trying to prove the theory false (which is what good scientific experiments are designed to do)—that is a good reason to conclude that the theory is true. In other words, if you repeatedly try to prove something false but can’t, that is a very good indication that it isn’t. The problem of underdeterminationIn reply, those whom van Fraassen calls “empiricists” often point to the “problem of underdetermination.” For any given theory that makes successful predictions about what happens in experimental conditions, there are countless other possible theories that make exactly the same predictions—and since they do, the experimental evidence in question is just as much reason to accept any of those theories as it is to accept our original one. Thus, the argument goes, we have no way of knowing whether our original theory is true, or one of the other “predictively equivalent” theories is true. SUGGESTED VIEWING How Occam's Razor changed the world With Johnjoe McFadden As an example of underdetermination, philosophers often offer this example. The evidence of fossils seems to provide reason to conclude that the universe is quite old; ancient fossils are what the “ancient universe” hypothesis predicts. But it’s also possible that God created an ancient-looking universe 200 years ago, complete with a “fake” fossil record for us to find, to make it look old. The existence of fossils is what that theory predicts too. So, the argument goes, the fossil record can’t be used as evidence that the universe is ancient; the fossil record supports the “200-year-old ancient-looking universe” theory just as much. The problem of underdetermination points out that, for any theory with supporting evidence, we could invent another completely different theory that predicts exactly the same evidence, and thus undermine that evidence’s ability to support the original theory.But this “argument from underdetermination” betrays a fundamental misunderstanding of what scientific reasoning is and how it works. To explain, let me use another rather strange (but very real and commonly discussed) philosophical thought experiment called “The Grue Problem.” The “Grue” ProblemSuppose I want to know what color emeralds are, so I observe a few, see that they all appear green, and form the theory that “all emeralds are green.” I thus predict that the next 100 emeralds I find will also appear to be green. And let’s say that happens, and so I thus conclude that my theory that all emeralds are green is true. Now, one might rightly point out that I don’t know for sure that all emeralds are green—I have not seen them all. Maybe some I haven’t found yet are blue. Fair enough. After all, we used to think that all swans were white, until we found some black ones. But let’s say that I go on a quest and collect every emerald in the universe—and, for the sake of the argument, let’s say I can do this, and can even know that I have every one of them. So, I collect them all, look at them all, and verify that they all appear green. Can’t I now rightly conclude that all emeralds are green?Inspired by the problem of underdetermination, a friend might argue that I cannot.Sure, they all appear green now—but there could be another kind of color called “grue.” Something is grue if it is green up to a certain point in time, but then spontaneously turns blue. And there could be an infinite number of “shades” of grue. Something that is one shade of grue will turn blue at noon today, but something that is another shade of grue will turn blue at noon tomorrow, etc. So yes, the emeralds appear green now; and since they haven’t turned blue yet, they are not some “past” shade of grue. But they might be some “future” shade of grue (e.g., they may turn blue at noon tomorrow). And since all future shades of grue are consistent with “being green up to this point in time,” the evidence you have is completely consistent with the notion that all emeralds are some future shade of grue, rather than green. Indeed, that they would appear green until now is what the “some future shade of grue” hypothesis predicts. So, we have just as much reason to conclude that all emeralds are some shade of grue as we do to conclude that they are green.You’re probably thinking “It’s not equally possible that the emeralds are grue; they are obviously green.” You are right! But explaining why your instinctive reaction to my friend’s argument is correct will help inform why van Fraassen’s “empiricist” is wrong and science actually does describe reality.The main mistake my friend makes is in thinking that the “empirical evidence” (of all the emeralds appearing green) is (or even should be) all I am using to draw the conclusion that all emeralds are green. It is not. I am also considering known facts about how colors typically work; things don’t usually change color, and when they do, they don’t do so suddenly, without cause, and all at once. So, even though the simple evidence of the emeralds all appearing green up to this point is consistent with them being some future shade of grue—that is even what the grue hypothesis “predicts”—it is still exceedingly unlikely that they are. The hypothesis that they are green is much more likely. Understanding science refutes the problem of underdetermination The misunderstanding about science that the “empiricist” pointing to “the problem of underdetermination” makes is similar to the one that my friend made. Science is not just about considering experimental evidence; in fact, it’s not even just about considering empirical evidence. As Ernan McMullin and many other philosophers of science have pointed out, the inference that makes science is “inference to the best explanation” (sometimes called “abduction” or “retroduction” by McMullin). While, depending on the circumstances, scientists use many different kinds of reasoning, science as a whole is, simply put, the process of considering multiple competing explanations and comparing them to certain criteria—explanatory criteria (the kinds of things explanations must be and do, by definition, to be a good explanation)—to see which explanation is the best.And these criteria do not deal only with empirical results. Yes, successful predictions raise the probability of a hypothesis, but it’s also the case that the more new assumptions a theory makes, the less likely it is to be true; every new assumption presents an opportunity for the theory to be false. (The fewer assumptions a theory makes, the simpler or “more parsimonious” it is said to be.) Likewise, the more existing evidence a theory contradicts, the less likely it is, because in order for a theory to be true, every piece of evidence it contradicts has to be somehow faulty. (The fewer established theories a new theory contradicts, the more “conservative” it is said to be.) And, obviously, the more something explains, the better explanation it is. (This is called having “scope.”) If a theory raises unanswerable questions, it’s not expanding our understanding, and thus is not wide-scoping. Scientists consider all these things when deciding which theory to accept, because the theory that adheres best to these explanatory criteria is most likely to be true.___the mere fact that a theory’s predictive success is why it “sticks around” or “becomes accepted” in the scientific community is not a reason to be skeptical about its truth.___The reason the grue hypothesis is no good is because it invents an entirely new kind of color—not just a new shade, but an entirely different category of color (a different way colors work)—and thus is not parsimonious. It raises unanswerable questions about how and why emeralds would just spontaneously change from green to blue (and thus does not have wide scope). And it contradicts what is already well established about how color works (and thus is unconservative).The theories that the problem of underdetermination points to do the same thing. Yes, the theory that God created an “ancient-looking universe” (complete with an ancient-looking fossil record) two hundred years ago is also consistent with the empirical evidence (of a fossil record) that presently exists; but that theory is monumentally unparsimonious (it requires many extra assumptions about infinite entities) and not wide-scoping (it raises unanswerable questions about why God would do such a thing). So, I can rationally conclude that it is false.Indeed, the history of science includes many examples of theories that were rejected because they lacked parsimony and/or scope, even before their falsity (and the truth of their competing theory) was confirmed by observation. As I point out in my book, geocentrism was rejected by the scientific community because it lacked parsimony, almost 200 years before the observation of parallax confirmed that the Earth moves around the sun. And the continuum theory of matter was completely rejected by 1860, because it couldn’t explain chemical reactions or organize matter into a periodic table, even though the experiments that eventually confirmed atomic theory weren’t even proposed until the 1870s. Solving the best of a bad lot problemIn response, the “empiricists” are likely to object, this time pointing to the “best of a bad lot” problem. “We have no reason to conclude that an explanation that has been shown to be better than others is true because we have no guarantee that the true theory was among those that we were considering.” If you have a “lot” (a collection) of poor explanations, even the best one is not true.The responses to this problem, however, are numerous. Peter Lipton argues that the set of hypotheses that scientists consider are not just randomly selected and thus unlikely to contain a theory that is true; they use existing knowledge to home in on what is most likely to be true. A doctor trying to explain abdominal pain is not going to bother wondering whether demons are causing it; they are going to stick with things like appendicitis and kidney stones, because they are most likely. Further, despite its name, inference to the best explanation is not just the process of comparing hypotheses and accepting the best one; we also want one that is a good explanation in its own right. If it’s not, we are going to keep looking until we find an explanation that is. And while that process does not guarantee that we will come across the exact truth, it’s very likely that the theory that emerges as the best will be at least approximately true, and thus we will be justified in believing it. And lastly, as I point out in my book, although many theories not based in scientific evidence (like geocentrism and continuum theory) have been completely overturned, science almost always progresses by the refinement of scientifically established theories—not their replacement. (Although our sun is not the center of the universe, heliocentrism was our first step in understanding the Earth’s true place in the universe.) So even if a theory we accept today may not be completely right, accepting it is a step on the journey toward the complete truth. The example of atomic theoryNow, it’s worth pointing out that most empiricists are not skeptical of all scientific theories; they are only skeptical of the ones that hypothesize the existence of “unobservables.” It’s not like they think that round Earth, heliocentrism, and germ theory are just useful (but untrue) “instruments” for making predictions about how to most efficiently navigate the seas, predict planetary motion, and treat diseases. They admit that the Earth actually is round, that the planets revolve around the sun, and that germs exist and cause disease. These facts and entities can be observed; the theories that suggest they exist are true. It’s only when theories start hypothesizing the existence of unobservables—like electrons, or quantum fields—that can’t be observed directly, that we should start doubting the theories’ truth. And to be fair to van Fraassen, in this published work, he doesn’t really say that we should doubt the truth of such theories. Only that scientific reasoning does not rationally force us to accept them as true. Skepticism, or agnosticism, he argues, is warranted. SUGGESTED READING Science is based in metaphor By Andrew Reynolds But the history of atomic theory throws a monkey wrench into that argument. Atoms used to be unobservable; again, scientists first accepted the theory that they exist because it had such grandiose explanatory power. But then atoms were seen with electron microscopes. They thus moved into the category of the observable. But this didn’t substantially change anything about what scientists were justified in believing; it certainly didn’t change any “atomic skeptics’” minds. It just confirmed what everyone already knew! If the hypothesis that something exists clearly provides the best explanation for what we can observe, then the belief that it exists is what is rational. The fact that the thing itself is not technically observable does not make doubting its existence rational.What’s more, the atoms were seen with an electron microscope. But electrons are themselves unobservable. How can an electron microscope reveal an atom if electrons are not real? This leads us to what is famously known as Hilary Putnam’s “miracle argument.” It’s (not) a miraclePhilosopher Hilary Putnam’s miracle argument is somewhat famous. Basically, he argued that a scientific theory being able to repeatedly make successful predictions—even about unobservables—without being at least approximately true would require a “miracle.” In other words, it would be such an improbable occurrence that it could not rationally be believed—the better explanation for why scientific theories about unobservables make the right predictions is because the unobservable entities and structures they hypothesize exist.Van Fraassen has addressed this argument. Indeed, in his original article, where he references Alison Gopnik’s point about orgasms not being “necessary for procreation” even though the desire for orgasm “drives the creation of progeny,” he is pointing to his own argument about how organisms are not naturally selected by evolution to get true beliefs; to the extent that belief-forming processes are selected for, the ones that are selected are the ones that are useful for survival—not the ones that produce true beliefs. In the same way, van Fraassen argues, scientific theories are accepted, not because they are true, but because they aren’t falsified; they make successful predictions; that’s what makes them “stick around.” So, the fact that they make successful predictions (and thus became accepted) is not a reason to think they are true.This argument is similar to C. S. Lewis’s “argument from reason,” which he used to argue against evolution: “The truth of evolution undercuts our ability to know that it is true.” Lewis’ argument famously failed; Elizabeth Anscombe, by Lewis’s own admission, demolished Lewis in a debate on the topic, and I have explained elsewhere why modified versions of the argument fail as well. In short, it’s because it fails to recognize that a belief-forming process can make an organism more likely to survive because it reliably produces true beliefs. It is therefore not the case that beliefs generated by naturally selected belief-forming processes are automatically false or unjustified.In the same way, the reason a theory “sticks around” could be because it’s not falsified, because it “makes correct predictions.” But the reason it makes correct predictions is most likely because it is true. (In pointing this out, I am echoing the arguments of Musgrave, Lipton, Psillos, and Kitcher, who refuted van Fraassen’s argument and analogy long before his 2024 article.) It would be a huge coincidence that it could do so without being true. And that is the point of Putnam’s miracle argument. Thus, contrary to van Fraassen’s suggestion, the mere fact that a theory’s predictive success is why it “sticks around” or “becomes accepted” in the scientific community is not a reason to be skeptical about its truth. ConclusionLet me close by saying something about the fact that empiricists don’t doubt the truth of all scientific theories, just the ones that hypothesize unobservables. In today’s society, this theory is dangerous to espouse publicly. The nuance between being skeptical about all of science, and just the highly technical theories about unobservables, is guaranteed to be lost to the average reader. And there is so much unjustified skepticism and doubt about the findings of science and experts that a headline like “Science Does Not Describe Reality” could easily fuel the anti-science movement, worsen climate change denial and cause the next pandemic.This is why I believe it was important to still respond to van Fraassen’s article, a full two years after he wrote it. Not only, as I have argued, does it represent a philosophically inaccurate view of how scientific reasoning works and what scientific reasoning can do, but it is a dangerous view to boot. It should thus be rejected.
September Monthly Review: Health MCP Guy?
For all the time I spend talking about APIs and data exchange, this newsletter has had embarrassingly little interoperability of its own. It’s old-school SaaS, baby - UI or bust. Not all of that is my fault! Substack, for all its popularity, is (as mentioned before) really frustrating as my system of record. The primary user it optimizes towards is the reader, whose attention feeds the app, the Notes feed, and the recommendation network that Substack is actually selling. Health API Guy is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Subscribe They’re falling into the same trap that Medium once sprinted into, albeit at a much more glacial speed. Younger generations may not remember (or never knew) it, but Medium once lured publications like The Ringer and Signal v. Noise onto its platform, only to lose them as it rebuilt itself around a paywall and an algorithmic feed. Substack’s original pitch circa 2020 was the antidote (you own your list), but every new feed feature chips away at it. I get it: writers are generic supply in the eyes of the Substack product team. Generic supply follows demand, so the consistent pressure on the PMs is to generate demand, which leads to every product cycle going toward discovery (Notes, recommendations, the app, live video). The end result lackluster author tools (laggy and broken analytics are truly crippling) all despite the premium price point. The archive is where it crosses from authorial gripes to actual reader impact, though. Across Substack and LinkedIn, I’ve published 1,218 posts and nearly 900,000 words since 2018. Substack’s native search can see only the 464 posts that live on Substack, and even there it’s woefully inadequate at surfacing relevant content (even for the guy who wrote it)! Readers have the same problem, writ large. Ask the Archive Fixing search (for both my readers and my own use) turned out to be extremely non-trivial, unfortunately: There’s no public API for readers to access content RSS exists for new content notification, but it only carries the 20 most recent posts and cuts paid ones off at the preview The only Substack MCP is an admin tool for analytics The export exists for authors, but it’s painfully awkward and slow. So I built something to work around that: the Health API Guy MCP. It’s a private MCP server holding the full text of everything I’ve written across Substack and LinkedIn. Add it to Claude or ChatGPT as a connector and you can ask things like: It pairs keyword search (for acronyms and case names, of which we have many) with semantic search. Every post is also labeled by topic, form, and court case, so you can pull a lawsuit’s (or multiple cases’) entire docket across Substack and LinkedIn in one query: Hail, Healthapiguyhydra This is also a bit of me eating my own cooking. I’ve spent the year arguing that headless healthcare is arriving and that developers want primitives over abstractions. Last week in Hail, Benihydra, I watched Salesforce plug its platform into Claude and bet that the records underneath outlive whatever interface sits on top: Salesforce must believe that the Hydra’s immortal head is the records, permissions, and business logic (in that they will survive whatever happens to the interface). It felt a bit hypocritical to keep my own archive behind a Substack search bar. The archive is the body. Substack is one head, and now whatever tool you might use is another. Will the EHRs follow my lead? Probably not imminently, but one can hope! Why Founding Members Only The MCP is available to Founding Member subscribers. A few reasons: It costs money and time to run. Hosting, the database, Clerk usage and AI compute for search and labeling are significant operational costs (that increase with usage). Substack gives me no way to automate access. There’s no API to check whether someone is a paid subscriber, so every user is manual operations for now. It’s a beta. We’ll need to improve things and parts will break. I’d rather they break for a small group of dedicated readers who will tell me about it. The Founding tier deserved a real benefit. Until now it was mostly a generous tip. Now it comes with something. If you’re already a Founding Member, reply to this email with the address you’d like provisioned. If you’re not and want in, upgrade here. Larger teams (such as companies) can get access too: group subscriptions at the Founding tier come with the group discount. The admin for the subscription can reply with the list of addresses to provision. Get 20% off a group subscription Pricing Founding membership is now a flat $200 a year, replacing the old suggested $150 that readers could adjust. Existing Founding Members will have access grandfathered in at their previous rate. Month in Review Articles Published Make Networks Dumb Again (Sep 11): AI is making old analog networks cheaper to use and flooding them with machine traffic in the process. A plea for agent-native rails with the intelligence at the endpoints, and for Washington to drag them to ubiquity. Interoperability, Unbuttoned (Sep 29): Interoperability is a series of workflows in a trenchcoat, and this post finally takes the trenchcoat off. A color-coded map shows which provider workflows went digital, which are fragmented, and which still run on fax. Video Content Antitrust’s System of Record Problem (Sep 3): The FTC’s investigation into Epic prompted a ninety-minute webinar, now posted with chapters and a smoothed transcript. We get into why market definition, missing B2B share data, and the SSNIP test leave antitrust poorly suited to systems of record, plus why information blocking may be doing more than any pending lawsuit. The Information Exchange: Cerner Milking Edition (Sep 18): This was so fucking fun. Ryan Tucker, Ryan Brickner, Brad Thorson, and I try an Around the Horn format, complete with points, penalties, and a mute button. We debate whether Oracle Health is dead, who would actually buy Cerner (IBM enters the chat), p(Doom), and why the front desk still hands you a clipboard. Regulatory Ask Not What Your Network Can Do (Sep 23): CDC’s RFI on public health data intermediaries lists use cases already served, unevenly, by eCR, lab reporting, IZ Gateway, and syndromic surveillance. The real opportunity sits in one question about AI: a network that can handle the next emergency without another interface project. Court cases Particle v. Epic: The Naughty Schoolteacher (Sep 4): After a summer-long vigil, the answer on Epic’s early summary judgment bid is two paragraphs and a remedial assignment. Particle advances to the next grade, and market definition gets another year of discovery. The Epic Discovery Files (Sep 8): Texas’s motions to compel arrive with a 251-page appendix of requests, objections, and meet-and-confer letters with Cravath. Inside: Epic using generative AI for document review, denied interoperability requests in scope, and Noerr-Pennington raised against lobbying discovery. Epic v. Health Gorilla: “Working as Designed” (Sep 9): Epic wants nothing to do with the data breach MDL, and explaining why puts fresh discovery on the public docket. The spiciest allegation: Health Gorilla told GuardDog to scrub its law firm business from its website instead of cutting off access. Veeva v. Epic: Legal Bypass Surgery (Sep 15): Veeva asks the Wisconsin Supreme Court to skip the Court of Appeals, while law professors and three policy groups line up as amici. Meanwhile, Epic’s lawyers apologize for another round of citation errors, including a quote that never existed. Texas v. Epic: Behind the Black Bars (Sep 17): The court portal served up Epic’s unredacted filings, revealing a $5 million document review budget and the AI workflow behind it. Also inside: the 200-plus company names Texas wants searched, and one very expensive Zoom invitation. OpenEvidence v. Doximity: Consequences Will Follow (Sep 25): OpenEvidence tells the court it will not comply with a discovery order, and its own lawyers at Quinn Emanuel say they won’t defend the choice. Add years of Slack reported unrecoverable, and Rule 37 sanctions come into view. Health Tech Keeps Choosing Violence (Sep 28): Doximity moves to end OpenEvidence’s case, Epic asks Texas to show its work, and a sleepy Audacious Inquiry patent fight sprouts antitrust and information blocking counterclaims. The main event is a long-sealed Cognizant v. Infosys ruling that hints where system of record antitrust claims can survive. EHRs One Verb for Oracle Health (Sep 14): Oracle’s earnings call quantifies every data center to the decimal point, while Oracle Health gets a single verb: “accelerate.” Panning the few healthcare mentions turns up an agentic care management system, a research-to-care ledger play, and the question of whether healthcare gets Larry’s patience. Epic’s Forretress Under Siege (Sep 30): Judy Faulkner tells a panel Epic paused hundreds of projects to harden its software and calls it a “shame,” while a spokesperson insists the roadmap hasn’t changed. Project Glasswing, a Pokémon-branded QAN sprint, and a trove of Jodel grievances reconcile the two Epics and preview the Jevons paradox coming for all software. Industry Analysis Scanning for a Network (Sep 1): Scan.com raises $220M to build the imaging network labs never got, speedrunning Zocdoc’s consumer-to-B2B pivot. Its wedge to network density may be the most American one available: personal injury litigation. The Front Desk Wants the Damn Whole Building (Sep 16): Hello Patient buys Converse Health, pushing its AI front desk into referrals, chart work, and prior auth. The copilot categories keep blurring, and your distribution partner is still your final boss. Cross-industry Comparisons A Different Patchwork Quilt (Sep 10): Healthcare loves to envy open banking, but the US version has no mandate, a toll booth at Chase, and data quality problems of its own. The grass isn’t greener; it’s another American patchwork quilt, and perhaps a worse one. Hail, Benihydra (Sep 21): Salesforce brings its platform into Claude, Slack, and its own agent, inviting the interfaces that might replace it. Cut off one head and more grow back, so long as the records underneath stay put. Living on A Trade Secret Prayer (Sep 22): Six credit unions are suing Fiserv, the Epic of core banking, by claiming their own member records as trade secrets. Banking has no Cures Act, so its lawyers reach for legal alchemy that healthcare has already tried. Other News None this month External Media Nabla Accelerate NYC: I kicked off fall conference season at Nabla’s Accelerate event in New York, where Delphine Groll opened by asking the room to picture the company it wants to become and the one it doesn’t. I liked her framework of bureaucracy, fear, and ego as the blockers. I also love vendor conferences/events in general - different vibe than industry biggies. Healthcare 101 with Nikhil Krishnan: I briefly guest lectured Out-Of-Pocket’s Healthcare 101 class. Appreciated Nikhil’s takeaways cover whether AI doctors can query HIEs, why healthcare’s data-liberation rules beat most industries’, and the hi-res graphic is in the comments. HCN: Epic Probed by the FTC: I joined the HCN guys to talk through the FTC’s investigation into Epic. Cedric’s new hairdo was an unexpected plot twist. The episode also covers MFN drug pricing, healthcare M&A and Eli Lilly’s acquisition streak. Fall Conferences: At eHealth Exchange’s Annual Meeting in Austin on Oct 27, I’ll moderate a panel on the tensions between AI, HIEs, and timely patient access with Jean Ross (Primary Record), Therasa Bell (Kno2), Byron Crowe (Doctronic), and Michael Marchant (Freenome). Here’s the rest of my schedule if you want to meet up: CommonWell (Redwood Shores, CA): Oct 13-14 Will be participating in a fun Jeopardy event Open@Epic (Madison, WI): Oct 20-23 Will be enjoying Verona, Willy Street, and other local adventures eHealth Exchange and Sequoia Project (Austin, TX): Oct 27-29 Yeehaw HLTH (Vegas): Nov 15-18 Groundhog Day, Venetian Edition RSNA (Chicago): Nov 30-Dec 2 See me at “Governing AI in Breast Imaging: What Health Systems Are Actually Doing” Digital Health Counsel 2026 AI Summit (Seattle): December 2-3 Will likely be speaking to a bunch of lawyers about information blocking Posts I Liked ChatGPT’s Epic integration: game changer or nothing burger?: Joshua Liu, MD offers five thoughts on OpenAI’s Epic launch, starting from the point that it rides the same open APIs available to anyone. He argues read-only access leaves ordering to Art and the ambient startups, and asks why HCA is piloting it alongside Commure. He’s sorta a must-follow at this point - consistently excellent, thought-provoking takes. Epic, Lilly, and the Discovery pass: Seth Chaney reads Epic’s first major Discovery deal (with Eli Lilly), as well as its revised developer terms on commercial displays, as the pipe finally opening between EHRs and pharma. Life sciences and health continue to collide. Scott Rossignol on EHR payer platforms and ePA fees: Scott argues the top ambulatory EHR vendors are turning the prior auth mandate into a per-member-per-year toll on payers, for an API whose operating cost has nothing to do with covered lives. His fix is two lines of regulatory text: put the CRD/DTR/PAS certification criteria in the Base EHR definition, and bring payer-facing ePA connectivity under § 170.404’s cost-based fee rules. It’s a good solution. Health API Guy is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Subscribe
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Quick hitters: O-line health, safety depth and Dan Campbell’s first days in Detroit with Glenn
Allen Park — Detroit Lions coach Dan Campbell and quarterbacks coach Mark Brunell met with the media on Friday. Here are the noteworthy items from those conversations. Healthier up front, banged up in the back It’s good news, bad news on the injury front. First, the offensive line is going to be far closer to full strength with starters Blake Miller (knee) and Christian Mahogany (hip) on track to return to the lineup. That provides stability the offense lacked against Buffalo, particularly at right tackle, where backup Larry Borom allowed 11 quarterback pressures and committed a trio of penalties. Subscribe However, with that same unit, veteran Ben Bartch (foot) is likely to miss Sunday’s matchup with the Jets. The left guard competition that’s been ongoing since May has effectively been whichever option is healthy that week. In the back end, safety Thomas Harper (ankle) is also unlikely to be available on Sunday. That leaves the team precariously thin at the position following Avonte Maddox going on injured reserve this week. Christian Izien is expected to get the start alongside Chuck Clark. “Izzy's been working a lot back there and had a full week,” Campbell said. “And he's gotten a ton of work this week, a ton of reps, full-speed reps. ‘This is what you're going to do, this is the calls’ and just dousing him with full-speed reps and he's done a good job this week.” Safety depth is the bigger concern. The team is expected to count on some combination of Jalen Mills, who signed to the practice squad on Monday, Bishop Fitzgerald, the undrafted rookie poached off the Steelers’ practice squad on Tuesday, and rookie cornerback Keith Abney, who doesn’t have experience at safety. “I'll say this about Abney, man, for a rookie, he's a pretty dang smart, conscientious, aware football player that's got a ton of room to really take off,” Campbell said. “…He's young. He's another one, he just needs reps and reps. But, if we need it, that'll be a guy who may have to go in for us.” You can check here for the full injury report, with game designations, later this afternoon. Reflecting on the past Responding to comments made by Jets coach Aaron Glenn this week, Campbell reflected on his earliest days with the Lions, before the coaching staff had been fleshed out and it was just he and Glenn at the facility working through what they wanted things to look like. “It was just he and I in the lab,” Campbell said. The coach said the two would fill the whiteboard that remains in current coordinator Kelvin Sheppard’s office top to bottom with notes about philosophy, coaching style, team identity and the type of players they wanted to target. “He looks different than me,” Campbell said. “I'm taller, I'm whatever. He's quicker. All these different things, man, but we're really the same. I mean we're so much the same. And he's the defensive version, I'm the offensive version. He was my right hand man. …It was fun, man. Those were good days.” Campbell said it was one of the best and worst days of his life when the Jets hired Glenn to be their coach. “AG means the world to me,” Campbell said. “He's one of my dearest friends because I know what he's made of. “…It's because you know you're losing a little piece of you. That's what he meant to me and to us. So, that's hard.” Traits under center A couple of weeks back, Sheppard noted that Brunell had identified Saints quarterback Tyler Shough as the best prospect at the position ahead of the 2025 draft. On Friday, Brunell confirmed his evaluation and explained what he looks for when studying a young quarterback. Here’s the full answer: “Young quarterbacks, you have to look at everything, you know? I look at guys coming out of college just like I look at any free agents that we might be looking at, or guys that we might add to our roster. Do they take care of the ball? Are they on time? How is their decision-making? How are their feet? “It's tough because you look at a college player, you don't understand what they're trying to do offensively, what their reads are, but you can identify when a guy is accurate, obviously, and when the ball's getting there on time. If there are a lot of interceptions, it raises a red flag. And I think with a lot of the spread offenses of what you're seeing, when you see a young player and they're running some pro concepts and he's having to make protection calls, and he's getting the right play out of the run game, and when there's a lot on his plate and he's executing it very well, and he's managing all of that, that really jumps out at you. It’s really hard to find. “That's one thing we saw with Luke Altmeyer. He had a lot of experience. We call it, ‘Hey, he's playing quarterback.’ And what does that mean? It's not just completing passes. It's getting guys lined up, getting the right play, getting the protection call right, just fixing some problems, being able to progress (through reads). And there's still some young guys out there that can do that at a high level, which is good to see.” Regarding Altmyer, who competed for the team’s backup job through the offseason and currently resides on the practice squad, Brunell acknowledged physical development slows once the season starts, because there aren’t reps to go around. However, there’s still extensive mental development that’s ongoing. “The key for him is approach the game as if you're the starter, mentally,” Brunell said. “And that's really all you can do. Approach the game as if you're the starter and be good in the (class)room. You come in alongside Jared (Goff), and you come in alongside Josh (Dobbs) and (do) whatever they need. And if you get an opportunity to talk to Luke, he'll tell you he does have a lot of responsibilities besides just getting donuts for us on Saturday. “For him, it's mentally staying focused, and even though there's really no chance this Sunday of him playing, he has to approach it as if he's taking the first snap and playing the whole game. So what's our game plan? What are our checks? What are we anticipating? And then during the game, we keep him involved as far as looking at coverages and pressures. And so, really, for him, it's just a mental game. And for now, that's all we can do.” Reason for more zone The Lions have significantly increased their usage of zone coverage on defense this season. I asked Campbell if that was a reaction to their personnel or driven by the focus to generate more turnovers, given it can be easier to produce interceptions when you can keep eyes on the quarterback while playing zone. “I think it was a little bit of both,” Campbell said. “We just felt like this would suit us a little bit better up to this point, and then be disruptive and get takeaways, which worked well Week 1. We had two (opportunities) last week against Buffalo we weren’t able to get, but they’re there.” I followed up by asking how much the combination of heavy blitzing with the back end playing zone has contributed to some of the early-season coverage woes, since adding extra players to the pass rush means leaving the coverage short-staffed. “I mean, it’s challenging, and that’s why a lot of the things we’ve done in zone, for the most part, have been to reduce that stress level back there,” Campbell said. “But that also requires the front getting there. And if you don’t get there, we already kind of talked about that, but there (has to be) a trust there.” The alternative, Campbell explained is sending four and it taking longer for the rush to get home, which can create different problems for a defense. “You can bleed yards,” Campbell said about the strategy. “It gets a little longer and it’s dink-and-dunk and run after catch. …So, we do what we think is right by what we feel like our personnel (does well). But also the game plan, who you’re going in to play, the matchups, their offense. “We’re not stuck on one way.” Detroit Football Network is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Subscribe
Pioneer of China NewCo model sued in US over trade secret misuse, double-dealing
A legal feud unfolding in New York is putting a spotlight on the work of a business development veteran who is credited for pioneering one of biopharma’s hottest dealmaking mechanism: the China “NewCo” model. In a lawsuit originally filed in New York state court and recently moved to federal court, China’s Lepu Medical Technology has alleged that biopharma business development consultant Su Zhang, who was hired to help shop its GLP-1 weight-loss candidates to Western partners, engaged in corporate double-dealing and trade secret leaks. According to the complaint, while acting as Lepu’s primary dealmaking liaison for a group of obesity and metabolic disease drug candidates, Zhang was secretly double-dipping as the acting chief business officer for a direct competitor, BrightGene Pharmaceutical. “She never adequately disclosed the role, never sought Lepu’s consent, and never proposed any safeguard,” Lepu alleged in its complaint, which was filed in July after Zhang’s consulting firm, CoDevCo, sought certain transaction-based success fees from its angry customer through an arbitration process in Singapore. Lepu, the parent company of Lepu Biopharma, has asked Zhang to pay back its $500,000 retainer and disgorge all benefits she received during the alleged breaches of fiduciary duty, plus other damages and relief. The company has also requested the court grant injunctions to protect Lepu’s trade secrets. The ill-fated partnership officially kicked off in December 2024, when Lepu tapped CoDevCo as its “exclusive business development mechanism” to identify collaborators for the company’s drug candidates. According to Lepu’s complaint, Zhang personally negotiated and signed the agreement as managing director for CoDevCo, which used her home address. Before the Lepu deal, Zhang made a name following a short stint as the global head of business development for Hengrui Pharmaceuticals. It was during her tenure that Hengrui signed a landmark deal granting exclusive rights for a portfolio of GLP-1 assets to Hercules, which was at that time newly established by a group of private equity and venture capital firms. In addition to the regular upfront and milestone payments, Hengrui also gained an equity stake in Hercules, which later became Kailera Therapeutics. The Hengrui-Hercules deal opened a new paradigm, where a Chinese biopharma company spins off certain early-stage assets to investors for further development through the creation of a new company abroad. The “NewCo” model quickly came into vogue as it allows Western investors to access high-potential assets originating from China at an early stage while giving the Chinese licensors an opportunity to reap long-term benefits through equity stakes in the new firms. The NewCo model proved its value when Kailera staged a record-breaking $625 million IPO on Nasdaq this April, merely two years into the Hengrui deal. Related Kailera CEO 'knew we were in a good spot' before obesity biotech's record-breaking $625M IPO On her LinkedIn page, Zhang described her work at Hengrui as “[b]uilding team and capability from the ground up,” forming NewCo and major pharma partnerships worth billions of dollars. Lepu clearly wanted that kind of track record to help boost its own cardiometabolic portfolio, which includes a range of assets for obesity, Type 2 diabetes, fatty liver disease and muscle preservation during weight loss treatment. “Lepu’s pipeline is very valuable, but only if Lepu could secure the right international partner to expand into the overseas market during the available commercial window,” the company argued in its complaint. The Chinese biotech said it had little knowledge of U.S. laws, customs or business practices in the business development field, and therefore “needed to rely entirely” on the expertise of Zhang and her team as the firm’s first engagement of a U.S.-based BD consultant. “Zhang’s dominating influence on the business development strategy is further evidenced by the fact that she personally controlled the business-development communications on behalf of Lepu with potential partners,” Lepu said in its complaint. After entering the deal, Zhang introduced Lepu to her four associates. According to Lepu’s version of events, all of them were allegedly employed at different time points to perform similar jobs at other Chinese companies that Lepu described as its competitors, while having access to Lepu’s confidential information. As such, Lepu described Zhang’s team as “a roster of individuals whose primary professional loyalty, by virtue of their concurrent full-time employment, ran to Lepu’s competitors.” As well as the specific examples set out in the case, a look at Lepu’s deals over the period suggests Zhang may have been involved in at least one transaction. During their partnership, Lepu, through its subsidiary Shanghai Minwei Biotechnology, also out-licensed its GLP-1/GIP/FGF21 agonist MWN105 to a NewCo called Sidera Bio in the fall of 2025. The deal included an upfront and near-term payment of $35 million, up to $1.01 billion in milestones, and a 9.99% stake in the Danish startup. It seems likely that Zhang facilitated the Minwei deal given that Lepu is on record as having used CoDevCo as its “exclusive business development mechanism.” The big shock for Lepu came in the form of a news article on June 25, 2025. The article, reporting on phase 2 data for BrightGene’s GLP-1/GIP receptor agonist BGM0504, identified Zhang as acting chief business officer of the Lepu rival. Blindsided by her association with BrightGene, Lepu confronted Zhang in July 2025. “Lepu was given assurances that there was nothing to be concerned about and told that Zhang would explain the matter to Lepu,” Lepu alleged in its complaint. “Zhang never did.” Lepu claimed that Zhang had the motive and opportunity to steer potential prospective partners toward BrightGene or other competitors. Later, in February 2026, one of Zhang’s associates joined BrightGene as the vice president for global business development, according to the complaint. Around the same time, Lepu sent written demand letters asking Zhang to account for her BrightGene role, identify what confidential data were shared with the rival firm, and provide any conflict-of-interest or firewall policies during the engagement. According to Lepu, neither CoDevCo nor Zhang answered the questions in their responses. Related Novo vs. KBP: How a $1.3B deal turned into a fraud accusation and an international legal fight In a motion to dismiss filed with the U.S. District Court in the Eastern District of New York on Sept. 4, Zhang’s legal team argued that Lepu’s agreement was signed with CoDevCo, and that an employee of the contractor does not owe fiduciary duties to the client. In its complaint, Lepu said: “That CoDevCo was the contracting entity does not insulate Zhang from personal liability for duties she personally undertook and personally breached.” Taking the argument one step further, the defending party argued that the consulting agreement “does not create a fiduciary relationship even between CoDevCo and Lepu; instead, it identifies CoDevCo as an independent contractor retained to market Lepu’s business to potential western partners.” Although CoDevCo was Lepu’s exclusive business-development contractor, there were no terms stipulating that the consulting firm should serve only Lepu, Zhang’s lawyer noted. As to Lepu’s claims that Zhang misappropriated trade secrets, the defendant argued that Lepu authorized the use of the information so Zhang’s team could perform their service per the agreement. In a rebuttal filed on Sept. 11, Lepu’s lawyer set out why they believe the Chinese biotech satisfied New York law’s misappropriation definition by alleging that the defendant used a trade secret “in breach of a duty or through improper means.” As an alternative to dismissing the suit, the defendant suggested the action should be stayed pending outcomes from the arbitration of a separate case in Singapore. While NewCo pioneer Zhang is defending her business arrangements, momentum behind the NewCo trend has continued unabated into 2026. Through August, Chinese biotech assets have spurred 15 NewCo deals this year, according to local trade publication PharmaDJ.
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In August, Pablo Torre Finds Out and Science Vs released an episode about my theory that electromagnetic fields from the electrical substation beside the 49ers facility may be contributing to the team’s run of soft-tissue injuries. As the originator of the theory, I was also a subject of the episode. I sat was interviewed by Wendy Zukerman and Rose Rimler of Sciene Vs. I sent them research, connected them with scientists, and spent hours digging through the City of Santa Clara’s and Silicon Valley Power’s records to help clarify critical details. Both Wendy and Rose came off as affable and professional, showing curiosity during the interviews, with Wendy going out of her way to question the “conspiracy theory” framing itself. Then they titled the episode We Solve the 49ers Viral Conspiracy Theory. I was familiar enough with their catalog that I never expected them to agree with my theory, but I did expect them to give it a fair hearing and to deliver their findings honestly. On both counts they came up short. They were not directly dishonest in anything they said, but rather in what they left out, in how what remained was cut, and in the picture painted by those two things in combination. They asked me to recorded the interview on my phone for better audio quality, and I held on to my copy for reference later. That turned out to be a fortuitous decision. Here is the raw audio of my first interview, unedited*. Only my side was recorded, so their questions aren’t on it, but you can generally infer them from the answers, and every claim I make below about what I said can be checked against my statements in this clip. (Note: Wendy had connection trouble at the beginning of the interview and was cutting in and out, which accounts for the false starts.) 0:00 -1:19:13 Audio playback is not supported on your browser. Please upgrade. Science Vs is a fun show. It is pitched at roughly a high-school understanding of science, for an audience that is skeptical, Snopes-oriented, and worried about misinformation. Take a claim circulating online, interview a supporter of the claim, interview consensus scientists, and then tell people which side of the line it lands on. I have listened to their episodes on raw milk, seed oils, 5G and other contested issues in the wellness space. I have problems with all of them, but each at least made an honest attempt to represent the actual range of scientific opinion by talking to credentialed scientists with differing perspectives. Dissenting researchers were heard from, answered, and often given a chance to respond. This episode did not do that. This article is not a relitigation of the science. I have written extensively about that already. This post is for the record. It is simply an accounting of what was wrong with their episode. Contents Is there a power plant next to the 49ers practice facility? — the clearest single example of getting something objectively wrong For the record — a high-level overview of all of the problems with their investigation Draw your own conclusions — why they had to make this episode at all What they left out about childhood leukemia — the exposure threshold, and playing games with statistics to minimize sick children What they left out about the mechanism — the body of literature they refused to cover, and evidence for the mechanism used against it The scientists Science Vs interviewed and did not air — four credential scientists who support myhe theory, recorded and cut, or not even called How they misrepresented me and my case — an answer severed from its question, and three telling edits How you would actually study the injuries — it doesn’t actually matter which team is the most injured, overall The theory: magnetic fields, oxidative stress, and collagen Since the episode never states my theory, here it is below. Those who are familiar with my work can skip this section. Electrical equipment produces magnetic fields, and those fields induce faint electrical currents in anything that passes through them, including people. My argument goes further than induced current. Mitochondria — the structures that generate a cell’s energy — run on continuous flows of electrons and protons, and those flows carry faint electromagnetic fields of their own. Maxwell’s principle of superposition shows that when two fields share the same space, they add together. An external field does not need to be strong to alter an internal field, it only needs to be present. The electron transport chain inside the mitochondria leaks a small fraction of its electrons by design, and those become reactive oxygen species — free radicals, which healthy cells use as signals. External magnetic fields cause the rate of leakage to change, increasing free radicals. When free radicals accumulate faster than the cell’s antioxidant systems can clear them, the result is oxidative stress. Oxidative stress is a recognized driver of chronic illness, including cardiovascular disease, neurodegeneration, diabetes and cancer, and it is in every medical school curriculum. One of its ordinary effects in connective tissue is that it switches on matrix metalloproteinases — MMPs, the enzymes that break collagen apart — while suppressing new collagen synthesis. Tendons are made of collagen. An athlete loading his soft tissue heavily six days a week is already creating oxidative stress in the tendons, so the addition of magnetic field exposure compounds the damage and inhibits repair, making him more susceptible to injury when enormous force lands on a tendon in a fraction of a second. That is the theory. We know that EMF causes oxidative stress, and we know that oxidative stress degrades collagen. The only thing missing is a study showing that direct connection. I have never claimed certainty that the substation is contributing to the elevated injury rate. I do believe it is likely, and I believe it warrants caution, and that a revenue machine like a major NFL team can easily afford to remove the exposure out of precaution. Is there a power plant next to the 49ers practice facility? Here is the clearest single instance of the problem with this episode. It requires no knowledge of electromagnetic fields at all. This story first came to me through Jon Feliciano, a former 49er, in an interview on Willard & Dibs on 95.7 The Game. Asked about why the 49ers are always injured, he said players used to joke that it was the power plant behind the practice fields. Wendy Zukerman corrects him on air. “It’s important to say that it’s not a power plant near the 49ers site.” Torre then asks her to explain the difference between a substation and a power plant. Her answer: a power plant generates electricity and transmits it to a substation, which converts the voltage into something your house can use and sends it on to your home or your business. There are two problems with that. The first is that there is a power plant on that site. The Gianera Generating Station is a natural-gas-fired peaker plant owned by Silicon Valley Power, and it has been there since 1986. I have published aerial photographs of the location from 1987 in which the gas plant is the only thing standing, before the practice facility was even there. I even mentioned the gas plant in my first interview. (Feliciano has since gone on record about this issue, and it is clear he had the substation in mind rather than the gas plant.) The second is that her definition describes a distribution substation, and the facility beside the 49ers is not that. It is the Northern Receiving Station, which takes in bulk power from outside the city’s grid and delivers it to distribution substations. Silicon Valley Power’s own map distinguishes receiving stations from substations, and Rose Rimler even reads the label out loud in the episode when she walks through that map on air. A few minutes before the map segment, Zukerman tells Torre: “like I said, we fact check everything.” Well, maybe not everything. I made a mistake On the morning of July 6th, at 10:20, I sent Rose and Wendy two studies. During the interview I had been asked which human studies show oxidative stress from electromagnetic fields, and I had not been able to name one on the spot. Rose emailed asking for the studies, I quickly searched for a couple, and I wrote that I thought these were the most relevant from that search. Unfortunately, I was busy and did not read either one closely at first. I picked them because they were topically relevant — one on substation workers, one on power plant workers. Neither were great studies, and their problems go past the ones raised in the episode. That was careless on my part. There is context that did not make the episode, though. Before that email I had been on a Zoom call with Rose talking about EMF and oxidative stress, and I pointed her to Dr. Henry Lai at the University of Washington, who has spent years aggregating the literature on this question. His tallies show that roughly 90% of studies since the late 1990s find oxidative effects from electromagnetic field exposure — hundreds of studies, systematically counted. Rose told me she was already aware of his work. So when she asked for studies, I understood her to have the aggregate view already and that she would report anything within that context. Not reading those two carefully was still a mistake, but the larger mistake was assuming the episode would be based on a thorough review of the actual body of literature, rather than on whatever I happened to send that morning. The second email At 1:49 that same afternoon — three hours and twenty-nine minutes after the first — I sent them a second email that I had been preparing for a while. It was a structured document in six numbered sections, written in response to a request they had made two weeks earlier, laying out my entire argument with citations attached to every link in the chain. The episode aired on August 13th, five weeks later, and not a single item from the second email is in it. Here is how it opens: The full email is included at the bottom of this post in Appendix B. Nearly 1,500 words in total. It contains two named mechanisms with the physics behind them. Occupational studies in humans. The literature on oxidative stress and collagen. A section addressing the strongest counter-evidence against my own theory, which I raised myself. And a closing section stating plainly what the theory cannot yet show. My entire argument, in writing, with detailed citations for every claim, provided to them five weeks before broadcast, and none of it made it into the episode. That is the single largest omission, but it is not an isolated one. The whole episode is riddled with similar problems, and the conclusion they came to is not merely a difference of opinion about the scientific evidence. Through omission and through strategic editing, Science Vs misinformed its audience — about what the evidence shows, about what I argued, and about who they spoke to. That is a notable outcome for a show whose stated purpose is correcting misinformation. For the record I am not going to tell you that Science Vs set out to discredit me, or that they had come to their conclusion before they reported the story, or that they used misleading editing to make me look like a man retreating from his own theory. I cannot know what was in anyone’s head, and I am not going to pretend otherwise, either. What I can tell you is what is on the record. They asked me for evidence and aired the weakest thing I sent. They interviewed three scientists who supported my theory and aired none of them. They discussed childhood leukemia without ever saying the exposure level at which it appears. And they took an answer I gave weeks before Ken Karipidis, the one EMF scientist who was put on air, was interviewed, and placed it directly after his critique, where it comes off as a major concession. A friend of mine who has worked as a journalist for thirty years read that last one and called it sleazy. I agree with her. Those are just the four issues that are impossible to defend as pure editorial decision, but they are not the only issues. The most glaring issues stem from what they left out: The exposure level at which the childhood leukemia association actually appears — three to four milligauss, a number the episode never states despite it being much lower than what I measured. The mechanism itself: The episode gets as far as “oxidative stress could weaken collagen,” which leaves it sounding like speculation, rather than a known pathway. The second email, and all the studies in it. Dr. Paul Héroux at McGill, whose work my proposed mechanism rests on, whose contact details I supplied, and who was never called. Dr. Beatrice Golomb at UC San Diego, who runs a research group on oxidative stress and mitochondrial function and has specific expdertice in collagen, interviewed and not aired. Dr. David Carpenter at Albany, the most prominent academic voice on the harm from magnetic field exposure, interviewed and not aired. Dr. Joel Moskowitz at Berkeley, interviewed and not even credited. The specific, testable condition I put in writing that would make me abandon the theory. My own unprompted statement of the theory’s evidentiary gap. My caveats about my own measurements. My ranking of EMF as one factor among several rather than the only one. The new equipment installed at those facilities between 2010 and 2014, and the sharp rise in system load from 2013 onward. But that is not all. What they kept, they selectively edited to serve a narrative that was not served by the raw transcripts of the interviews. A description of thousands of commercial routers in a workplace, reduced to the Wi-Fi in your house. My own acknowledgment, multiple times, that "I'm not a scientist" clipped in an episode that spends considerable energy pointing out that I am not a scientist. And a qualification I volunteered about my own measurements, cut from my answer and delivered later by their EMF expert as a correction. Together their edit produce a portrait of a wellness guy with Wi-Fi phobia and two bad studies, backing away from his theory the moment a “real” scientist looked at it. A practice facility where nothing changed because no new substation was built. Injuries written off as random because the 49ers were not quite the single most injured team in the league over the period in question. That portrait is false even though almost no individual statement made in the episode is. Draw your own conclusions At the top of the episode, Pablo Torre says his show had been flooded with requests to investigate the substation — that it was the thing they were asked to look into over and over again. Neither show went hunting for this story. It arrived from their own audience, in volume, and it could not be waved off. A thread I posted on X reached twenty-two million people. A guy with a gaussmeter and a brand-new Substack obligated a Pultizer prize winning program to spend an hour on a question about player health, that is considered fringe enough that most media operations won’t touch it. Pablo Torre Finds Out could not ignore it. So Science Vs came in and ran a “debunking” operation instead of an investigation. Everything below is what had to be left on the cutting room floor to deliver the “debunking”. They could not ignore it. So they tried debunked it instead. The demand was strong enough to force an episode, and since the episodes release the 49ers have sustained more injuries, including season ending ones, and interest has only grown. Demand from fans and playets is strong enough to force a better investigation from someone else. An omission is not a lie until you find out what was omitted. What follows is the detailed record so you can see the full picture. Draw your own conclusions. I have drawn mine. I am going to keep publishing. A note about Pablo Torre Finds Out After the episode aired I posted publicly, calling out Pablo Torre Finds Out for concerns I had about the integrity of their investigation, and about an interview directly with Pablo Torre which had been offered but never happened. I have since spoken with a producer at PTFO. The offer had rested on a misunderstanding about where things stood between us, and it fell away as the Science Vs part of the production widened past the science. He apologized for the miscommunication and I accepted. The producer also confirmed to me that they did essentially hand off the entire investigation to Science Vs for narrative purposes — so Pablo would be genuinely curious or potentially surprised by their findings — while still taking responsibility for what went out under their name. I appreciated the candor and the accountability, and I am comfortable with where we left things. So this post is not about PTFO. My disagreement is with Science Vs. What they left out about childhood leukemia Childhood leukemia appears at three milligauss. They gave no number at all. 1. They built an EMF ruler, then discussed childhood cancer without it. The sequence on air went like this: First I measured almost 9 mG, then I measured up to 50 milligauss. Torre reacts with concern — “that sounds high.” Cut to Karipidis: the public limit is 2,000 milligauss. Torre reacts again — “What happens at 2,000?” Karipidis explains that nothing happens at 2,000, that safety factors are built in. Then: at more than 50,000 milligauss you get flickers of light in the retina, and higher still, nerve stimulation. The listener now has a ruler (their ruler) to measure these numbers with. Fifty is nothing by their ruler. Then the episode turns to childhood leukemia and states, accurately, that there is a real association — but tellingly, they never give the exposure level at which that association appears. Childhood leukemia appears at three milligauss. They conveniently left that out. The pooled analyses that produced the World Health Organization’s carcinogen classification found roughly a doubling of childhood leukemia risk above three to four milligauss. That is the number that belongs in that segment, and it is more than ten times below the reading that had just been dismissed as trivial. I gave them that number myself, on tape, in the interview. Describing my own threshold, I said my comfort level for long-term chronic exposure is three to four milligauss, but preferably one. 2. Six children in thirteen million. The episode reports that these fields might explain one to four percent of childhood leukemias, then reframes it as a German estimate of perhaps six cases among thirteen million children. Torre, to his credit, is uncomfortable. What never gets explained is why that number is small. Almost no children lives above three milligauss in Europe. Fewer than two children in a hundred, in the Italian data. So even if the risk to those children doubles, the number of additional cases across an entire country stays small — not because the hazard is small, but because hardly anyone is exposed to it. Count the whole population and the few who are exposed disappear. And the reason hardly anyone is exposed is that siting rules keep housing away from transmission lines. In Europe, at least. The Dutch government has a standing precautionary policy against building new homes in any zone where the annual average magnetic field exceeds 4 milligauss — the same number the episode never mentioned. Denmark and Norway treat 4 milligauss as the level that triggers a look at mitigation. That is five hundred times below the ICNIRP figure quoted on air. The United States has no federal equivalent. That is evidence of infrastructure siting policy working. It is not evidence that there is no hazard. It is evidence that we already act as though there is one. If you listen to the raw audio you will hear that my proposed solution is EMF exposure is to build better infrastructure. What they left out about the mechanism 3. They accused me of cherry-picking, and then cherry-picked themselves. On air, Zukerman tells Torre that people who worry about electromagnetic fields dismiss the studies showing null results and collect the ones showing harm, and that this is why you have to be careful not to cherry-pick. They had two papers I had rattled off in a hurry, and a second email containing a carefully chosen set. They ran the two weakest, graded them on air, and presented the result as the state of the evidence for not only my theory, but the whole question of oxidative stress from magnetic fields. That is cherry-picking from my emails. The bigger picture is what they did with the literature as a whole. Zukerman acknowledges it exists, dismisses it, and disposes of it in a single stroke. You can go online right now, she tells Torre, and find scores of studies showing these fields increase oxidative stress. The issue, she says, is that they are not studies in people. Many of them are in people. The occupational studies in my second email are in people. That email had been in her inbox for five weeks. She waved off the literature on a factual claim that the documents in her possession contradict. (I have written separately about the evidentiary standard at work here). The effect was that they essentially baited me: ask the subject to supply the evidence, take the weakest thing he sends, and let that stand as a proxy for the whole argument. Wendy has been doing this show for ten years and clearly knows how to extract what she needs for her desired narrative. 4. They presented the collagen-improvement research as a gotcha, but I had already addressed it. The episode treats the existence of studies showing that EMF can improve collagen as a surprise that undercuts me, but I had pre-emptively addressed that five weeks earlier in the email they ignored. Those studies use measured, high-intensity pulsed dosing. The mechanism by which they work is oxidative signalling. The cell reads a controlled rise in reactive oxygen species as a warning, upregulates its antioxidant defenses, mounts a repair response, and the therapy stops before the system is overwhelmed. The key point is that it induces an oxidative response, which means those studies are actually evidence for my proposed mechanism, not against it. A field that produces a therapeutic effect cannot be biologically inert (which is the implication when they say “Nothing happens at 2,000 milligauss). Chronic ambient exposure is the same pathway with no off switch, and it is most consequential during the evening and while sleeping, when the body is in repair mode and the exposure does not stop. Section 5 of my email is titled What about the study showing improved collagen synthesis. I raised the counter-evidence myself, explained why I did not think it refuted the theory, and wrote that I was disappointed the question had not come up in the interview. That is worth holding against the cherry-picking charge in the item above: the studies they presented as inconvenient for me were studies I had gone out of my way to put in front of them. 5. Section 1 of my email stated a critical argument that was never put to the expert directly responsible for it. My email says the exposure limits exist to prevent acute effects and do not address chronic exposure at all, and that my dispute is with the entire framework. Zukerman gestures at this once. After Karipidis gives the 2,000 milligauss figure, she tells Torre that I would object because those levels do not capture “more subtle effects.” That is not my argument, and “subtle” is doing a lot of work here. My argument is that the limits are built to prevent acute effects — nerves firing, muscles twitching, etc — and were not designed to address chronic exposure at all. In fact, ICNIRP’s own documents state as much themselves. Mine is a structural objection to what the standard measures, reduced as a concern about subtlety, it becomes a matter of degree, rather than a categorical difference. They interviewed Ken Karipidis, vice chair of ICNIRP — the body that writes those limits. He was asked what the limit is, but he was never asked how it applies to chronic exposure. The scientists Science Vs interviewed and did not air 6. They interviewed four officials of the standards body. The episode credits roughly a dozen researchers. Four of them are associated with ICNIRP. Ken Karipidis is the vice chair. Rodney Croft chaired ICNIRP from 2020 to 2024 and led the development of its current guidelines. Dan Baaken is ICNIRP’s scientific secretary. Frank de Vocht sits on the Main Commission. One of them speaks in the episode. Their institution’s position is more than adequately represented — the 2,000 milligauss figure, the safety factors, the assurance that nothing happens below the line. 7. The four who were left out. Dr. Beatrice Golomb is Professor of Medicine at UC San Diego — a physics undergraduate degree, a PhD in biology, an MD. She directs a research group whose stated focus is the relationship between oxidative stress, mitochondrial function and health. That is the mechanism the episode spent its first half dismissing. Her published work includes the fluoroquinolone case series behind the FDA’s black box warning on an antibiotic class that ruptures tendons, where the accepted mechanism is oxidative stress and mitochondrial toxicity — the back half of my chain, already on a drug label. She is in the credits. She is not in the episode. She has told me she finds my theory biologically plausible, and that she has a recording of her interview. Dr. David Carpenter directed the Institute for Health and the Environment at the University at Albany for decades and is the most prominent academic voice arguing these fields cause harm. Childhood leukemia is the reason these fields carry a WHO classification at all, and Carpenter is the person you call if you want that case made by someone who has spent a career on it. He is in the credits. He is not in the episode. He has told me that when he was interviewed they could not have been less interested in what he had to say. Dr. Joel Moskowitz directs the Center for Family and Community Health at UC Berkeley’s School of Public Health. He told me directly that they interviewed him and that he thought it went well. He does not appear in the episode, and unlike Golomb and Carpenter, he does not even appear in the credits. Dr. Paul Héroux at McGill is the researcher whose work provides the foundation for the oxidative stress mechanism my theory rests on. I gave Rose his email address and phone number. He was never interviewed. They never even called him. 8. “He’s not a scientist.” The episode leans hard on the fact that I am not a credentialed scientist. Zukerman says it. Torre repeats it. “At all.” Having built a segment on that, they then left out the physicist-biologist-physician, the professor of public health, the director of a university environmental health institute, and the McGill researcher whose work the primary mechanism comes from. They spent the episode telling their audience I am not a scientist, and then kept four actual scientists who support the theory off because their argument does not survive otherwise. How they misrepresented me and my case 9. They played my words as a response to an interview I had never heard. Near the end of the hour, Zukerman says she went to me and told me the evidence was lacking. Then she plays me saying I am not wedded to it being an EMF, that I have staked my reputation on it needing more study, and that I am not certain of anything. That segment was placed immediately after Karipidis had finished taking the cherry-picked papers apart. It plays as a man folding under expert scrutiny. Commenters have used it against me since, but it is incorrect. Here is the sequence as it happened. I was interviewed. Karipidis was interviewed weeks later. I was never told what he said, or even who he was. I was never asked to respond to it. I did not know his name until the episode aired. That is not a simple editing decision. That is a quote from one interview, moved to follow a critique from a different interview it was not a response to, so that it would land as a concession. A friend of mine who has spent thirty years as a journalist read that sequence and called it sleazy. She is right. The full passage is reproduced in Appendix A, and it is worth reading. What airs is the preamble. Four paragraphs later I say “to directly answer your question” — and that answer, about what would change my mind if the team relocated, is not in the episode. Neither is the sentence two paragraphs on, where I say the EMF might turn out to be ten percent of the problem. I will say the underlying point again, though, because I meant it and I still do. I am not wedded to my theory that magnetic fields from the substation are contributing to the 49ers injuries. I could be wrong. What I am wedded to is the process of scientific inquiry, and the fact that we should be cautious around these exposures and we need more independently funded studies. 10. Three telling edits. They cut “I’m not a scientist” mid-sentence. What I said: “...and I am not certain of anything. I’m not a scientist. To me, I find the mechanisms compelling. I will go back to the fact that I got into this not because of the 49ers, but because of clients I was working with who suffer from EDS...” What aired: “...and that I am not certain of anything. I’m not.” The clip ends on the first two words of the sentence in which I say I am not a scientist, in an episode that spends considerable energy establishing that I am not a scientist. The full sequence is in Appendix A. They cut my own description of my work. Asked what I do, I said I run a wellness business, that I am focused on writing software to help people navigate environmental stressors, that environmental health is my focus, and that I also do independent journalism and research. What aired is the wellness business and the environmental health, with the software and the journalism removed from my own answer. The software engineering does come up later — narrated by them, as a hacker who grew up to write firmware — but my current work, in my own words, arrives as “wellness guy.” Thousands of commercial routers became home Wi-Fi. What I described: working at a wireless networking company surrounded by thousands of Wi-Fi routers, and a stress-induced health collapse afterward that working in that environment contributed to. What aired: Wi-Fi, the kind you have at home — reinforced by a clip of Christian McCaffrey talking about turning his router off at night. Three cuts, and every one of them makes me seem less credible. That is not a coincidence. 11. I gave them my own caveats and the test that would disprove me. In the first email I wrote that a well-designed chronic, ambient-level exposure study in tendon showing no collagen degradation, run over many months, would undercut my confidence in the theory. That is a specific, testable condition, stated in advance and in writing. There was a second interview, weeks later, which was not used in the episode, but in that I asked again for the falsification criterion to be included. What the episode presents instead is a man saying “we need more study,” which reads as a hedge, an open-ended request for the benefit of the doubt. It is the opposite of a hedge. Section 6 of my second email says, unprompted, that as far as I am aware there is not a single study showing EMF-driven oxidative stress degrading collagen in a human in vivo or in human tendon in a lab. I wrote that because it is true and because it is the first thing anyone should check. Under their standard it becomes the hinge of the entire first half, framed as something they had to surface without my cooperation. I had handed it to them five weeks earlier. And in the interview I said that my 25 to 50 milligauss readings were taken at knee level, and that these fields attenuate quickly, so by the time it reaches your head it is not that high anymore. That did not air either. The qualification arrives later, from Karipidis, as a correction. How you would actually study the injuries 12. They measured the wrong thing. The episode spends its final act on whether the 49ers are the most injured team in the NFL, finds no clean ranking, and lands on “injuries are random”. That is the wrong test. You would define the exposure — measured field levels at the facility — and the outcome narrowly: soft-tissue injuries, not a single MSK injury count that a broken finger and a ruptured Achilles both land in. Then you would compare the 49ers to themselves before and after the exposure changed, and compare that change against every other team over the same window. That controls for league-wide shifts in rules, turf and training load. It is a difference-in-differences design, and it is standard. I sent them that argument on July 28th, in writing, along with the fact that in eleven of the past twelve seasons the 49ers had finished top ten in Adjusted Games Lost. And by the episode’s own reporting, the 49ers are second in games lost to injury over the past decade, with FTN’s Aaron Schatz confirming that once you adjust for starters they come out second worst in the league — after having been one of the healthiest teams for years before that. A finding like that is where an investigation starts, not where it stops. 13. I did a lot of substation research for the episode that was never aired. I had reported that the substation next to the facility was expanded in 2014. That was wrong, and Rose Rimler and I sorted it out together. They gave me credit on air, which I appreciated, but framed it as a concession on my part to something they had found. In fact I had been investigating it myself, was uncertain before they asked, but was waiting for clarification from Silicon Valley Power. The uncertainty centered around a substation named “Esparanca” that was proposed right behind the facilities as part of the stadium construction, but now appears to never have been built. I spent days in Silicon Valley Power’s records, and did eventually reach Silicon Valley Power for confirmation and indentified the mistake myself. I also gave them highly detailed documents on what we do know about those facilities: new equipment installed between 2010 and 2014, and load growth across the system with an inflection around 2013–2014, with the Northern Receiving Station carrying the highest capacity in the system and sitting closest to the data center corridor. None of that is in the episode. I have a separate piece about it coming out soon. *I cut 2 seconds from the raw audio to remove personal information that had no connection to anything in the episode. Appendix A: the passage the clip was taken from This is the sequence from my first interview, in full. The episode uses one fragment of it. It’s tricky because my understanding is that there’s something like a 15-year half-life on collagen remodeling issues. They’re going to get a new crop of players. What I really need, though, is for the injuries to be broken down so we can see the soft tissue injuries. Right now, they’re categorized as MSK injuries, but let’s say we can actually identify them more specifically. Is that right? He was able to do that? Oh, cool. I wasn’t able to find that information. Interesting — I didn’t know that data existed. I tried so hard to get it, and I didn’t know it was available. Maybe you could connect me with that person. That would be amazing. I’m not wedded to it being an EMF, honestly. I’m not. I would say that, to a certain extent, I’ve staked my reputation on the fact that it needs more study. It’s important to look into it, and I am not certain of anything. I’m not a scientist. To me, I find the mechanisms compelling. I will go back to the fact that I got into this not because of the 49ers, but because of clients I was working with who suffer from EDS, Ehlers-Danlos Syndrome, a tendon hypermobility issue. This condition is documented to be partially caused by oxidative stress. I’ve worked with them to mitigate their EMF exposure and have seen people improve. I think it’s a bigger story. In a way, the 49ers represent an occupational cluster with specific exposure risks. If someone would conduct a study on this, I believe we could learn a lot. Perhaps we would discover that it’s like, okay, maybe it’s 10% of the problem. I don’t know the exact number, but I think either way, conducting the study would provide valuable insights. To directly answer your question, it’s challenging for me because it’s part of a bigger story. If the 49ers move and stop having injuries, I might conclude that it was related to the substation. However, if they move and still experience injuries, I would want to analyze the nature of those injuries. Are they primarily soft tissue injuries? I don’t think it’s necessarily a case closed, but the story might lose traction at that point regardless. Three things are worth noting. The aired fragment stops immediately before the sentence in which I say I am not a scientist — the cut described in item 10. It also stops four paragraphs before the words “to directly answer your question.” What the episode plays is the throat-clearing. The actual answer, about what would change my mind, never airs. And two paragraphs in, I say the EMF might turn out to be ten percent of the problem. That is the ranking the episode says I never gave. Appendix B: the full email, July 6th, 1:39 PM Hi Rose, You asked me to send you some studies a couple of weeks ago. I apologize for the delay. I have been incredibly busy. I also wanted to give you a chance to dig in yourself, and get your own perspective before I influenced you too much with mine. That said, I do want to make sure that the actual argument is abundantly clear, so here it is! One note before I begin, there are really two separate questions here: Does the substation cause the soft-tissue injuries? That was my specific claim, and what the podcast is about. Is the theory biologically sound? Can 50/60 Hz fields at these levels do anything biological below the safety limits? Question two is why people have been calling me a conspiracy theorist. The regulatory and advisory bodies (ICNIRP, etc) maintain that anything below their exposure limits is biologically inert, and that position is broadly accepted within the mainstream, but the actual science paints a different picture. To defend my theory I’ve had to defend a much larger claim: that the advisory bodies have the biology wrong. I can’t honestly answer question 1 without first addressing that. Here’s is a simplified outline of my theory, with links to studies: 1. Advisory body thresholds for biological effects The ELF magnetic-field limits (ICNIRP’s ~2,000 mG public / 10,000 mG occupational) exist to prevent acute effects from exposure. If a magnetic field is strong enough, it makes nerves fire and muscles contract. Muscles twitch. You can see faint flashes of light in your vision. People can even feel tingling or even a shock. That happens due to Faraday’s law, which states that a time-varying magnetic field induces an electric field inside the body via the creation of Eddy currents.The standards assume that those currents do nothing below the twitch threshold. They do not consider chronic effects at all. My argument is that they are biologically active and do have chronic effects. 2. There are multipe ELF-EMF mechanisms for inducing oxidative stress. This is basic biophysics. Below are the two primary mechanisms. Simplest first. Dr. Paul Héroux of McGill has the most intuitive explanation, which rests on Maxwell’s principle of superposition: because Maxwell’s equations are linear, two sets of electromagnetic waves sharing the same space simply add together. In the interview I pictured a pebble dropped into a pond, sending out clean ripples. Then a boat motors past at distance, sending larger waves, and where they meet the ripples, the two add together and the original pattern gets distorted. In our cells, the mitochondria run on continuous currents of electrons and protons that carry their own faint electromagnetic fields. An external field from a substation, by the principle of superposition, adds to those internal currents and shifts the pattern. The electron transport chain in the mitochondria leaks a fraction of its electrons by design as reactive oxygen species (ROS), which act as signalling molecules in a healthy cell. Distorting that field increases that electron leakage, creating oxidative stress. A tiny electromagnetic interference results in a large downstream effect. https://www.sciencedirect.com/science/article/pii/S2405844025006474 The more complex pathway is Dimitris Panagopoulos’s Ion Forced-Oscillation / Voltage-Gated Ion Channel (IFO-VGIC) mechanism. Weak, polarized, low-frequency fields force the ions (calcium, potassium, sodium) next to an ion channel’s voltage sensor to oscillate; because that force scales with the inverse cube of the distance involved, fields far below the stimulation threshold can still force the channel open, disrupting the cell’s ion balance and driving ROS overproduction (Nitric oxide and superoxide interact and produce peroxynitrite, a highly unstable cytotoxin that breaks down into free radicals). https://www.researchgate.net/publication/366088934 https://www.spandidos-publications.com/ijo/59/5/92 https://www.mdpi.com/1422-0067/22/18/10041 https://www.frontiersin.org/journals/public-health/articles/10.3389/fpubh.2025.1585441/full https://pmc.ncbi.nlm.nih.gov/articles/PMC3772193/ 3. Evidence of oxidative stress, in vivo, in humans from ELF-EMF There are many studies, and the strongest are occupational, which applies to the 49ers situation. 115 power-plant workers vs. 145 office controls. Serum malondialdehyde (MDA, the standard lipid-peroxidation marker), superoxide dismutase, and catalase were all significantly higher in the exposed group, and the markers rose with increasing field exposure. https://journals.sagepub.com/doi/abs/10.3233/WOR-203244 A follow-up where they reversed the oxidative stress in power plant workers. A double-blind randomized controlled trial: 91 power-plant workers given vitamin E, vitamin C, both, or placebo for 90 days. The antioxidant groups showed reduced lipid peroxidation and raised antioxidant capacity versus controls. https://pubmed.ncbi.nlm.nih.gov/32191586/ A spot-welder study: 46 welders occupationally exposed at 50 Hz, showed significantly altered red-blood-cell antioxidant enzyme activity and concluded ELF-MF “might act as an oxidative stressor… even at the recommended levels of exposure.” https://pubmed.ncbi.nlm.nih.gov/18504600/ A substation-specific study found oxidative stress and DNA damage https://pubmed.ncbi.nlm.nih.gov/24460415/ 4. Oxidative stress degrades collagen This half isn’t controversial at all. Oxidative stress activates the matrix metalloproteinases (MMPs) that break collagen down and suppresses its synthesis. Here are three example studies: Siwik et al. 2001: Oxidative stress raises MMPs and lowers collagen synthesis in cardiac fibroblasts. https://pubmed.ncbi.nlm.nih.gov/11121376/ Fisher et al. 2009: Collagen fragmentation drives oxidative stress and elevates MMP-1 in aged human skin. https://pmc.ncbi.nlm.nih.gov/articles/PMC2631323/ Varani et al. 2006: Decreased collagen production in oxidatively aged skin. https://pubmed.ncbi.nlm.nih.gov/16723701/ 5. What about the study showing improved collagen synthesis I’m glad you asked this question, and I’m bummed we didn’t get to it in the interview because it is a great question, and very important to understand. Superficially it may appear to be a refutation of my theory, but I would argue that it actually supports the underlying argument. That study used a short, high-intensity pulsed dose: therapeutic-PEMF, the same type of field used clinically to stimulate bone and tissue healing. The reason this works is because it triggers the very same biological pathways that can lead to oxidative stress. The exposure still stimulates ROS production, but done at a controlled dosage, for a limited duration it has a different effect. The cell reads the ROS as a warning signal and it upregulates its antioxidant defenses, and mounts a repair/proliferation response. The therapy is then stopped before the cell gets overwhelmed. That is essentially a hormetic response: a small dose of a stressor producing a beneficial adaptation. Two things follow: At the very least, this means the field is biologically active, which by itself undercuts the regulatory claim that these fields are inert below their thresholds. There is a wealth of literature on PEMF (pulsed EMF) bone regeneration and calcium channel signalling (which is the second mechanims in section one). Here is one. https://www.nature.com/articles/srep13856 At best, it leads us straight to my actual concern, which is that under chronic, chaotic and unregulated exposure, the cell’s antioxidant capacity gets overwhelmed, resulting in oxidative stress. There are plentiful examples of things that are beneficial at controlled doses, but harmful at uncontrolled doses. Excecise is one obvious, uncontroversial example. Botox is perhaps a more interesting example. 6. What about a study that shows EMF causing collagen degradation in humans? As far as I am aware there is not a single study showing EMF-driven oxidative stress degrading collagen in a human, in vivo, or in human tendon in a lab. There are studies involving isolated fibroblasts though, which secrete collagen. The most relevant one showed that human fetal scleral fibroblasts exposed to 50 Hz ELF-EMF showed a significant decrease in collagen synthesis and that MMP-2 expression was upregulated, which is the exact mechanism I described in section 2. https://pmc.ncbi.nlm.nih.gov/articles/PMC3626379/ That’s it! Thanks again for the interview. Best, Peter Anthony Cowan Environmental Health · Wellness Tech · Researcher & Journalist Publisher & Editor, Living Energy Bio: petercowan.comSocial: X · Instagram · TikTokApp: sunlightis.lifePhone: [redacted]
Pathways Community raises money for mental health
Members of the Pathways Community and their staff served hotdogs and bratwursts to support upcoming mix and mingle events.