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Background: the answers and comments on this question prompted this question.

I know that when a new scientific theory is published there is a rush for people to devise experiment to prove or disprove it. However there is lot of research that involves original experiments that are not necessarily related to new not-yet-proven/accepted theories.

Now, obviously science relies heavily on peer-verification of theories and experiments, but are experiments today actually verified by independent peers?

The thread I linked to made me grow some doubts: if an experiment has so much trouble being funded, how is it possible to scientifically verify the results of already published data, especially of high-cost experiments. If there is no incentive in doing that verification, how can articles describing a new experiment be validated scientifically?

Disclaimer: sorry for the possible dumb question, but I had only a brief experience in academia at the beginning of my career (and it was in SW engineering, where "experiments" are way less common than proof of concepts software, so verification is a far less difficult subject there).

As a further explanation of my doubts, the last time I remember an experiment being rejected because it couldn't be validated was the thing about cold fusion by Fleischman and Pons, back in the late 80s. At least that was a case that reached mainstream media. I guess such events (both validation and rejection) are more common in the specialized journals, but I don't remember any other "big event" that reached the mainstream media since then.

Please, note well that I'm not claiming that experimental results never get published by the mainstream media, here I'm focusing on the validation by peers that are independent from the original authors/scientists.


Maybe I wasn't too clear, possibly because I didn't use the right terminology.

I'm not particularly interested in the review process details (although I welcome any correction about my lack of terminology), but in actual scientific validation of experimental results.

What I really care for is whether or not published scientific experimental results are effectively put under experimental scrutiny by the scientific community.

V2Blast
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  • If somebody else's result has some bearing on my research direction, it will probably end up being tested in my experiments. But that is not the same as replication. Testing a single strand is not often done, testing the interwoven results are. – Jon Custer May 17 '23 at 13:39
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    I think the problem with your question is the way it is phrased it appears that you think the academic peer review process involves experimental scrutiny. This occurs because the title of your question with the emphasized "actually" implies that this used to be the case or is claimed to be the case. – Bryan Krause May 17 '23 at 14:06
  • @BryanKrause Sorry. I already edited the question to specify that I lack the correct terminology. What I'm interested in actual application in academia of the "phylosophical" scientific principle of experimental validation. In particular when what is being validated is not some theory, but an experimental methodology. – LorenzoDonati4Ukraine-OnStrike May 17 '23 at 14:37
  • @BryanKrause To be bluntly concrete: if someone performs an experiment and publishes setup and results, how can the scientific community accept the results if no one has verified them? If the verification is only based on palusibility "on paper", doesn't that go against the very scientific principle of experimental verification of any claim? – LorenzoDonati4Ukraine-OnStrike May 17 '23 at 14:37
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    @LorenzoDonatisupportUkraine Best to be most blunt and concrete when initially writing the question. :) We're in a bit of a pickle here since there are numerous existing answers, so it's kind of too late to change the question. Being very concrete, are you asking specifically about novel methodology? Because this is quite different from simply an original experiment. – Bryan Krause May 17 '23 at 14:39
  • @BryanKrause To add even more info on my doubt: from many answers in this thread and other threads, it seems that acceptance by the scientific community is more often based on trust and not actual independent verification. But trust is not something objective, and can be influenced by many factors that have nothing to do with science (economics, politics, friendship, mutual interests, etc.). – LorenzoDonati4Ukraine-OnStrike May 17 '23 at 14:40
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    @BryanKrause I'm not making a difference between the two cases. The fact is that until I read the thread I linked to in my question, I was convinced that the scientific community had an habit of redoing experiments to verify the published data were reliable. In a sense, I was convinced that there were some sort of peer-checking mechanism for experiments similar to the peer-review system for papers. It seems I was wrong. So I asked this question. Sorry if it wasn't framed particularly well, but even as I'm reading the comments and the answers I begin to understand how to frame it better. – LorenzoDonati4Ukraine-OnStrike May 17 '23 at 14:47
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    @LorenzoDonatisupportUkraine I'm not sure you're noticing then the difference between peer review and the broader scientific discourse; the former is based a lot more on trust than the latter. But yes, you've correctly discovered that science is influenced by economics, politics, friendship, etc: science is done by people, and people are influenced by all those things. – Bryan Krause May 17 '23 at 14:49
  • @BryanKrause Well Ok, now I sound quite ingenuous :-) I know that the scientific institutions and scientists are involved, as any human activity, in economics, politics, etc. What I'm a bit perplexed is discovering that what I thought a fundamental distinctive trait of Science (I used the capital S, just to be clear :-), the distinctive trait I would argue, seems not so central as I thought it to be. – LorenzoDonati4Ukraine-OnStrike May 17 '23 at 14:55
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    I think you should do some research into the "Replication Crisis." Ongoing research by some Psychologists have found that they are unable to reproduce most published psychology findings, or they are but they find the effect is 1 to 2 magnitudes lower then the published effect... Some big experiments to mention are the Stanford prison experiment (Which we now know to be a poisoned experiment). – Questor May 17 '23 at 20:32
  • One of the suggested culprits is the positive hypothesis bias... And publish or perish. Journals have a tendency to not publish negative findings, so there is a push to throw out "bad" samples until a positive finding is achieved. – Questor May 17 '23 at 20:35
  • @Questor Thank you for the useful POV and info. – LorenzoDonati4Ukraine-OnStrike May 18 '23 at 07:48
  • @Questor And yep, publish or perish is really bad for science IMO. That's also why I dropped out of my SW engineering PhD 20+ years ago (not the only reason, but it was another nail in the coffin for sure). It really didn't fit my bill. – LorenzoDonati4Ukraine-OnStrike May 18 '23 at 08:16
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    When important claims appear, scientist are trying to validate or reproduce that in other experimental facilities, perhaps with slightly different methods. Like the ATOMKI claim of an X17 particle https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7738366/ that some CERN experiments are trying to reproduce. However, these experiments are often very specialized. – Vladimir F Героям слава May 18 '23 at 13:21
  • N.B.: If you want an example of high-energy failure to replicate, you don't have to go back to the 80's, as you could look at this failure in superconductivity reported two days ago. – Daniel R. Collins May 19 '23 at 02:48
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    @DanielR.Collins That's very interesting. Thanks. – LorenzoDonati4Ukraine-OnStrike May 19 '23 at 16:30

6 Answers6

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There are two related but separate processes in play here.

On the one hand, papers are peer reviewed, i.e., when you submit a paper describing your experiment, results and conclusions to a conference or journal, two to three peers will review it. They review the paper - they typically don't have the time, funding or other requirements to actually re-do your experiment. They will check whether your arguments make sense, whether the experiment you describe can in principle be used to address your research question, maybe run a small simulation.

On the other hand, people will try to replicate your experiment, i.e., run a similar experiment and see whether they get the same results. (Typically they will run a modification, because straight-up replications are very hard to publish, and publications are important to academics.) If you have an exciting result, many people will try to replicate and extend it. If then most of these people cannot replicate your results (take a look at the "replication crisis in psychology"), the excitement of your results will wane.

Stephan Kolassa
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  • Thanks for your explanation. So you are telling me that it's unlikely that an experiment will be replicated in the exact way its authors published it? I understand that some modification could be considered negligible from a theory verification POV, but aren't that modifications going to alter the experimental results, so potentially voiding the verification attempt (after all the original experiment could contain some kind of error that the modified setup could eliminate). Do I miss something? – LorenzoDonati4Ukraine-OnStrike May 17 '23 at 11:24
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    In the end, it very much depends, especially on the field. Very few fields allow you to exactly replicate an experiment down to the last detail, so some changes between experiment runs are inevitable. What people look for in replications is mainly a consistency in the patterns, not necessarily a perfect match: do all the results point in the same direction, or did someone get a surprising positive result, but the next 20 similar experiments all got a negative result? Yes, there is some subjectivity involved in when experiment B is a "true" replication of experiment A. – Stephan Kolassa May 17 '23 at 11:33
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    It can actually be bad if everyone does the experiment in exactly the same way. Repeating an experiment with changes helps to confirm that a particular part of the experimental methodology isn't having unforeseen effects on the results. – Technically Natural May 17 '23 at 13:00
  • @Yachsut OK, that I can understand. However if no one replicates the experiment in the exact same way then how can we be sure the experiment is valid?. Note that my question is not about validating the theory behind an experiment (in that case I'm sure different experimental approaches that give the same coherent results are indeed good). My problem is with work whose subject is the experiment itself (a new methodology, for example). In this case what can be said about that methodology if all the independent verification comes from different (albeit similar) methodologies? – LorenzoDonati4Ukraine-OnStrike May 17 '23 at 13:17
  • @Yachsut To me it seems like (sorry for the brutally simplistic analogy) someone claimed he could fix broken shoe soles using just nails and a screwdriver, then all other people tried to verify the claim using hammers and nails. Then everyone claims "OK, the method is sound, but I just used a hammer instead of a screwdriver to verify it". – LorenzoDonati4Ukraine-OnStrike May 17 '23 at 13:19
  • As above, there is always an element of subjectivity involved. The goal of a replication is to convince experts in this (or a closely related) field that the original method "worked" or not. "Worked" here carries various meanings: in a mature field, the broad outlines are known, and you are interested in what "works" for specialized details, and specialization gets narrower over time. Science is a social endeavor that works by Bayesian updating of beliefs. – Stephan Kolassa May 17 '23 at 13:22
  • @StephanKolassa So in the end it is getting toward the situation of some very specialistic research field in math (as a friend of mine working in math research told me), where the concepts are so abstract and difficult that there might be just one person that actually understand them all. In this case you don't get really a "peer" review. But that's math, which is not an experimental science, so "convincing" your colleagues (instead of "showing") could be considered close enough. – LorenzoDonati4Ukraine-OnStrike May 17 '23 at 13:45
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    @LorenzoDonatisupportUkraine in reality, people who read the paper just have to trust the experiment was actually done. If the writer of the paper lied, it creates a lot of drama and problems for them later... if they ever get caught. I'm sure many didn't get caught. – user253751 May 17 '23 at 19:30
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    @LorenzoDonatisupportUkraine If you do find replication with a slightly different experimental setup, it's even better for the underlying theory. We usually try to generalize in science, we aren't usually interested in findings that can only be observed under one very specific set of experimental conditions. If you don't find replication with a different setup, it is on the experimenter to convincingly explain why the changes in setup shouldn't have affected the results. – Nuclear Hoagie May 17 '23 at 19:46
  • @NuclearHoagie Yep, I'm aware of that. Sorry if I wasn't clear, but in a previous comment I stated that I did understand that the theory validation benefits from a palette of different experimental setup confirming the theory. What I'm worried of, however, is how one can confirm that an experiment with a given experimental setup actually worked. – LorenzoDonati4Ukraine-OnStrike May 18 '23 at 07:59
  • @NuclearHoagie Here is a very crude example of my doubts. Theory T foresee some experimental results. Team A devise an experiment EA that purportedly confirms the theory. Teams B and C perform slightly different experiments (EB and EC) that confirm T. So T is accepted as valid. However EA was incorrect (or rigged) in a subtle way, so it wouldn't have been able to confirm T. Since no one cared to exactly repeat EA, no one discovered that EA experimental setup cannot actually confirm T and the data from EA was wrong and happened to confirm T just by chance (or deliberate "forging"). – LorenzoDonati4Ukraine-OnStrike May 18 '23 at 08:02
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    @LorenzoDonatisupportUkraine In this case we have still obtained knowledge about the validity of theory T. That the wrong people might be credited with the 'discovery' is a shame, but only tangential to the purpose of the scientific process. That theory T was thought to be verifiable because of a mistake (experiment EA) is part of the messiness of science in practice. If experiments EB and EC would have disagreed with theory T, this would cast doubt on experiment EA, and it might then be (reproduced and) discarded as false. This is all part of the process. – Servaes May 18 '23 at 13:49
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    @LorenzoDonatisupportUkraine: Actually the math situation that you describe, with "just one person", is highly atypical. Abstraction is what mathematicians do. For most mathematical papers submitted for publication, there are multiple researchers able to understand the paper, and peer review is the norm. – Lee Mosher May 18 '23 at 16:58
  • @LeeMosher Sorry if I wasn't clear, but I just cited an extreme example I know of because of my friend told me about the issue. I didn't claim it was a common situation in math (in fact my friend actually works in a math research field where there are a lot of peer-reviewers). I just cited that example because of what StephanKolassa said in a comment of his (...and you are interested in what "works" for specialized details, and specialization gets narrower over time.) – LorenzoDonati4Ukraine-OnStrike May 18 '23 at 19:02
  • By that, I did not mean that there are fewer people who understand your work. I meant that advances are narrower in scope, simply because everyone agrees on the broad outlines of what works and what does not work in your field. – Stephan Kolassa May 18 '23 at 20:01
  • One important thing that people often forget, is that just because somebody else reproduced it or found statistical significance, doesn’t mean that you have statistically significant evidence for that person being correct, let alone for the result they got. In the end, even a highly reproduced, peer-reviewed paper is just hearsay to you until you verified you can rely on those sources. … In normal life, nothing is ever under that close scrutiny though, and we almost always blindly trust things, because otherwise even getting out of bed would be impossible as the floor may not exist. :) –  May 19 '23 at 16:20
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When laypeople are introduced to the idea of replication, they imagine scientists constantly redoing every paper that comes out, to "check it". At least I did. This is not the case in most mainstream sciences. The closest thing is when a paper is basically announcing the release of a software - then conceivably a lot of people might give it a try, since it's usually easy (or is it?) to just install and run a software on your computer.

This does not mean there is no replication. To be sure, there is a replication crisis, in the sense that we have too many studies that should be replicable but aren't. But it's important to remember that a lot of science can and is replicated.

The replication does not take the form of a researcher going to their PI, and submitting a 20-page document titled "Proposal for Comprehensive Replication of Jones et al. 2022". Replication is rarely a discrete project, it is embedded in novel research. The rare exception is extremely high profile and controversial work - for example, the Yamanaka induced pluripotency protocol inspired many outright reproduction attempts.

A lot of science these days is not "from scratch", but building upon and refining previous studies. Say Smith 2019 discovered that red M&Ms cure cancer in mice. Murphy 2024 might then test different chemical extracts of red M&Ms across various mutant mice, and discover that a specific chemical is responsible for the effect by acting on a certain gene - such a study might often begin with a "sanity check" by repeating a simple version of the original Smith 2019 experiment. Indeed the Smith 2019 regimen may serve as a baseline or control for evaluating the additional claims of Murphy 2024.

Another common situation is when published results are assumed to be true, and an experiment is set up such that if the assumption is false the experiment will produce nonsense results. For example, imagine that Dr. Murphy decides to feed some mice only the filling of red M&Ms, while other mice are fed only the shell. It's expected that either group will either be cured of cancer or not. But if all mice die of chemical poisoning, that obviously raises some questions about the results claimed in Smith 2019. It is often possible, with clever experimental design, to "cover" validation of past results as well as probe the actual hypothesis of interest.

You also mention cost. However, you make the false assumption that reproduction always costs as much as the original experiment. Think of it this way - if you decided to sail from Europe to America, would you need to be an equal to Columbus? A big sink of money, and time, therefore money, in original research is trial and error. There are a lot of unknowns about what experiment would work, so it costs a lot to perform it. However, reproducers can skip all that - with the benefit of hindsight they can avoid the false starts.

gomennathan
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    Thank you for the extensive answer. Particularly insightful the final part about skipping false starts. – LorenzoDonati4Ukraine-OnStrike May 18 '23 at 08:08
  • ... it's usually easy (or is it?) to just install and run a software on your computer - the nicest situation from my experience is when researchers provide a Jupyter notebook with their analysis, which anyone can run without needing to install custom software, preferably hosted on Colab; I wish this was more common. – yoniLavi May 20 '23 at 12:18
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Others have discussed the official process.

Generically, the thing is, the process is messy. There is no megalithic authority presiding over science, nor academia in general. We don't have a "king of science." There is no "pope of academia."

As such, it is possible for a false result to remain unchallenged in the literature for some time. This can be due to honest mistakes or actual fraud or various combinations.

The process of science eventually turns to re-examine old ideas. People are hungry for publication. There are teams and groups and milling armies of people hungry for publication. They search through old journal articles, read them, sit and think "I could re-do that experiment in a couple weeks with stuff in storage at the lab." And many variations on this. They re-do the arithmetic in published articles. They request the raw data. They compare other experimental results reported at other labs.

So, at any given moment, it is quite likely the literature contains many errors, mistakes, and a few (hopefully a very small number) of actual frauds. And science will try to correct them.

As Dara O'Briain said: Science knows it does not know everything. Otherwise it would stop.

Another thing that tends to happen is that a result becomes irrelevant due to advances that move us past it. As a trivial example that nobody probably cares about: Suppose somebody claimed they could make electronic vacuum tubes to perform a certain way, but that their result was wrong. The advent of transistors moved us away from vacuum tubes, so nobody cares anymore about the performance of tubes. Possibly such an incorrect result from 60 years ago might hang around in the journals and never get challenged. So there is a category of knowledge that one should take extra caution about accepting as authoritative, because the process of science dropped the topic.

So you can recognize a healthy science endeavour by the presence of people questioning the results. They need to be doing it in a well based manner, not simply sticking their fingers in their ears and going "la la la." They need to understand the issues, the theories, the current state of things. And then they need to be free to ask questions and make critiques. If there is nobody questioning a result that is a warning that the science has gone moribund.

Boba Fit
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    This is an important point. If the science "matters" (loaded term), you can bet it will be attacked and investigated thoroughly, like Pons and Fleischman. Invalidating those findings is important and publishable by itself. But if it doesn't "matter", like vacuum tubes, nobody's going to spend the time and money to bother. Science is a dynamic conversation where the interesting ideas keep going, and the boring tangents get left behind. – mightypile May 17 '23 at 22:02
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but are experiments today actually verified by independent peers?

In some (rare) cases, yes.


The examples that I have are in Computer Science, where there is a big push lately for articles to share their "artifacts", which are environments that allow to reproduce their results.

Major associations such as the IEEE and the ACM now have their own "badges" (IEEE badge and ACM badges) that are awarded only if the artifact is publicly available, if the results can be reproduced, and if the environment is "re-usable" (read, it's easy to tweak their plat-form to test another hypothesis).

Major conferences such as Discotec or POPL now have their "artifact evaluation committee" whose main goal is to check that the results from the papers can be reproduced.

Clément
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  • By "artifact" do you mean something that also include the source code? – LorenzoDonati4Ukraine-OnStrike May 17 '23 at 13:39
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    @LorenzoDonatisupportUkraine Absolutely. An artifact generally contain the source code, instructions to execute the program(s) and various configuration files. One example (disclaimer: that I contributed to) can be found at https://github.com/statycc/loop-fission#reproducing-results . – Clément May 17 '23 at 17:56
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    I can confirm this is the case, I did a PhD in computer science (machine learning) and towards the end of my candidature it became increasingly difficult to publish without also including a link to source codes, datasets and other artifacts that might be needed to verify the results. In general, this is a good thing, for me it was a challenge as my PhD was industry-sponsored making it hard to comply. – David Waterworth May 17 '23 at 22:44
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    @Clément Thanks for the added detail. – LorenzoDonati4Ukraine-OnStrike May 18 '23 at 08:09
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    @DavidWaterworth Interesting POV. Thanks. – LorenzoDonati4Ukraine-OnStrike May 18 '23 at 08:10
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No, peer-reviewers usually just read the manuscript. However with a lot of experience reviewers can often tell from the presented results and the methods description if the research is valid.

If researchers have doubts about the published results they usually do a replication study and then write a letter to the editor.

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I might be worth thinking about science from a Kuhn-ian point of view, rather than a Popperian one.

Start with the somewhat surprising assumption that all scientific conclusions are really models of how the world works, and that all models will eventually be shown to be false to some degree.

In Kuhn's model scientists conduct studies under the assumptions of the current Paradigm (i.e. the set of models that people assume to be true). As long as the results of those studies produce data that makes sense under the current paradigm, they support its truth/usefulness of the models that make up the current paradigm. To the extent that those studies propose new models, they become part of the paradigm. Thus we build up "sandcastles", each new theory based on the validty of the those that came before it, and the success of the new thoeries support the validity of the old. But over time, anomolous results accumulate that can't be explained by the current paradigm. At first these can just be ignored, or explained away, but eventually the weight of anomolies becomes so heavy that the models on which the whole paradigm collapses and you have a scientific revolution, or paradigm-shift. The things that survive this shift will continue to form the foundations on which the new sandcastle is built, and overtime will be compressed to form sandstone.

As well as happening at a macro-level (relativity replacing newtonian physics for eg), it also happens at a micro-level. If a paper is published proposing X and providing an experiment that supports it, rather than trying to replicate those results, someone will say "well, if X is true, then perhaps Y is also true", and they will conduct an experiment assuming X is true. If those results are positive, they lend support to X, if they fail, then the probably don't in one go disprove X, but they might start to add question marks to it. If there are enough such results, people will start looking round for other theories to based their investigations on. This usually doesn't happen in a big bang (like it would do at the macro-level), but mostly just people drifting away from believe X - its not demosntrated false, it just that those that don't base their science on it tend to be more successful.

One downside of this process is that it is slow, and at any one time only those with a deep knowledge of the whole field will really have a good idea of what the field believes to be true or not at any given time. In fact, at any given time it would be very hard for someone to say "here is a list of things that people in field A believe to be definately true". We will only really know what was a good call and what not decades or even centuries into the future.

This is of course no good when your results are needed for practical purposes (like treating diseaes). A couple of things to observe here is that even if we can't say for certain that X is true, if you had to bet your life on X or not X, you'd be better off betting on X, even if you only have a qualified belief in it being true. The second is that the medical and health fields are fields were replications really do happen. There are often multiple clinical trials into the effect of a particular exposure or class of drugs. These are generally collected together in meta-analyses which collate all to evidence for a single question to see what the evidence is in aggregate.

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    For better or worse, something often misunderstood by non-scientists is just how much easier it is to do science showing whether a treatment works than to figure out how it works. Another reason that medicine and basic science tend to use different approaches to replication. – Bryan Krause May 18 '23 at 14:56
  • Thanks for the interesting POV. I didn't know anything about the Kuhnian POV. – LorenzoDonati4Ukraine-OnStrike May 18 '23 at 15:37
  • @BryanKrause That's definitely true and it's largely due IMO because you have (a) strict regulations for researching and marketing new treatments or medical devices and (b) the prospect of huge lawsuits if something goes horribly wrong due to negligence, incompetence or sheer fraud. – LorenzoDonati4Ukraine-OnStrike May 18 '23 at 15:43
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    @LorenzoDonatisupportUkraine No, it's because it's a simple experiment to say does X change Y. You give X, you measure Y. Mechanism is far more difficult to assess, and many tests of mechanism are inconclusive, you might be measuring a separate correlate rather than something in the causal chain, and so most subsequent experiments will not try to exactly test the same thing again, there are just too many potential facets and targets. – Bryan Krause May 18 '23 at 16:36
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    @LorenzoDonatisupportUkraine Every child knows that if they throw a ball up it falls down again, but figuring out How Gravity Works is complicated. But you can still do a lot of useful stuff only with the partial result that stuff that goes up comes back down. – user3067860 May 19 '23 at 14:38
  • @user3067860 Sorry, but I don't get your point here. I didn't question the usefulness of any kind of experiments (even partial or minor ones). I just questioned whether or not an experiment could be considered valid if its results are not verified independently. – LorenzoDonati4Ukraine-OnStrike May 19 '23 at 16:00
  • @LorenzoDonatisupportUkraine That's in re: this current side topic about medical studies. In math you can prove something, e.g. we can prove that sqrt(2) is an irrational number. People don't necessarily need to re-do that over and over. In medicine things are very hard to prove but since the result is the important part you can do larger/repeated studies and come up with ideas about how things are without knowing why they are that way. Like throwing the ball up a bunch of times, measuring how hard you throw it, how high it goes, and how long it takes to come down. – user3067860 May 19 '23 at 16:20
  • @user3067860 Yep, I know that. In some comment I think I have also stated that math is no experimental science, so "experiments" are not its realm. I'm well aware of the difficulties of non-hard science like medicine (compared e.g. with physics or chemistry) where the systems are so complex that you don't even have a mathematical model to base your experiment on. However statistical methods are employed and also sound experimental practices (like double-blind testing). So, all these limits notwithstanding, you still can replicate an experiment. – LorenzoDonati4Ukraine-OnStrike May 19 '23 at 16:37
  • @user3067860 Of course what you can "prove" (in a statistical meaning) is that a drug can (say) be used to treat some disease with some percentage of success (reproducibly). And then you must assess whether or not that percentage is high enough to be significant, also considering side effects. – LorenzoDonati4Ukraine-OnStrike May 19 '23 at 16:37