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AI tools are spotting errors in research papers
- more_corn 2y agoThis is great to hear. I good use of AI if the false positives can be controlled.
- rokkamokka 2y agoFalse positives don't seem overly harmful here either, since the main use would be bringing it to human attention for further thought
- wizzwizz4 2y agoIs there advantage over just reviewing papers with a critical eye?
- jeffbee 2y agoIf reviewer effort is limited and the model has at least a bias in the right direction.
- wizzwizz4 2y agoSo I just need to make sure my fraud goes under the radar of these AI tools, and then the limited reviewer effort will be spent elsewhere.
- estarkio 2y agoI think some people will find an advantage in flagging untold numbers of research papers as frivolous or fraudulent with minimal effort, while putting the burden of re-proving the work on everyone else. In other words, I fear this is a leap in Gish Gallop technology.
- Zigurd 2y agoThere's probably 10 X more problematic academic publications, than currently get flagged. Automating the search for the likeliest candidates is going to be very helpful by focusing the "critical eye" where it can make the biggest difference.
- epidemiology 2y agoThe largest problems with most publications (in epi and in my opinion at least) is study design. Unfortunately, faulty study design or things like data cleaning is qualitative, nuanced, and difficult to catch with AI unless it has access to the source data.
- AlienRobot 2y agoHopefully, one would use this to try to find errors in a massive number of papers, and then go through the effort of reviewing these papers themselves before bringing up the issue. It makes no sense to put effort unto others just because the AI said so.
- nyrikki 2y agoWalking through their interface, it seems like when you click though on the relatively few that aren't just tiny spelling/formatting errors, Like this style: > Methodology check: The paper lacks a quantitative evaluation or comparison to ground truth data, relying on a purely qu... They always seem to be edited to be simple formatting errors. https://yesnoerror.com/doc/eb99aec0-a72a-45f7-bf2c-8cf2cbab1f4a https://yesnoerror.com/doc/eb99aec0-a72a-45f7-bf2c-8cf2cbab1... If they can't improve that the signal to noise ratio will be to high and people will shut it off/ignore it. Time is not free, cost people lots of time without them seeing value and almost any project will fail.
- imagetic 2y agoBreaking: Research papers spot errors in AI tools.
- topaz0 2y agoThis is such a bad idea. Skip the first section and read the "false positives" section.
- afarah1 2y agoI can see its usefulness as a screening tool, though I can also see downsides similar to what maintainers face with AI vulnerability reporting. It's an imperfect tool attempting to tackle a difficult and important problem. I suppose its value will be determined by how well it's used and how well it evolves.
- camdenreslink 2y agoAren't false positives acceptable in this situation? I'm assuming a human (paper author, journal editor, peer reviewer, etc) is reviewing the errors these tools are identifying. If there is a 10% false positive rate, then the only cost is the wasted time of whoever needs to identify it's a false positive. I guess this is a bad idea if these tools replace peer reviewers altogether, and papers get published if they can get past the error checker. But I haven't seen that proposed.
- xeonmc 2y agoLet me tell you about this thing called Turnitin and how it was a purely advisory screening tool…
- csa 2y ago> I'm assuming a human (paper author, journal editor, peer reviewer, etc) is reviewing the errors these tools are identifying. This made me laugh so hard that I was almost crying. For a specific journal, editor, or reviewer, maybe. For most journals, editors, or reviewers… I would bet money against it.
- karaterobot 2y agoYou'd win that bet. Most journal reviewers don't do more than check that data exists as part of the peer review process—the equivalent of typing `ls` and looking at the directory metadata. They pretty much never run their own analyses to double check the paper. When I say "pretty much never", I mean that when I interviewed reviewers and asked them if they had ever done it, none of them said yes, and when I interviewed journal editors—from significant journals—only one of them said their policy was to even ask reviewers to do it, and that it was still optional. He said he couldn't remember if anyone had ever claimed to do it during his tenure. So yeah, if you get good odds on it, take that bet!
- crazygringo 2y agoThis actually feels like an amazing step in the right direction. If AI can help spot obvious errors in published papers, it can do it as part of the review process. And if it can do it as part of the review process, authors can run it on their own work before submitting. It could massively raise the quality level of a lot of papers. What's important here is that it's part of a process involving experts themselves -- the authors, the peer reviewers. They can easily dismiss false positives, but especially get warnings about statistical mistakes or other aspects of the paper that aren't their primary area of expertise but can contain gotchas.
- yojo 2y agoRelatedly: unethical researchers could run it on their own work before submitting. It could massively raise the plausibility of fraudulent papers. I hope your version of the world wins out. I’m still trying to figure out what a post-trust future looks like.
- rererereferred 2y agoEventually the unethical researchers will have to make actual research to make their papers pass. Mission fucking accomplished https://xkcd.com/810/ https://xkcd.com/810/
- brookst 2y agoBoth will happen. But the world has been post-trust for millennia.
- GuestFAUniverse 2y agoMaybe raise the "accountability" part? Baffles me that somebody can be professor, director, whatever, meaning: taking the place of somebody _really_ qualified and not get dragged through court after falsifying a publication until nothing is left of that betrayer. It's not only the damage to society due to false, misleading claims. If those publications decide who gets tenure, a research grant, etc. there are careers of others, that were massively damaged.
- epidemiology 2y agoAI tools are hopefully going to eat lots of manual scientific research. This article looks at error spotting, but you follow the path of getting better and better at error spotting to it's conclusion and you essentially reproduce the work entirely from scratch. So in fact AI study generation is really where this is going. All my work could honestly be done instantaneously with better data harmonization & collection along with better engineering practices. Instead, it requires a lot of manual effort. I remember my professors talking about how they used to calculate linear regressions by hand back in the old days. Hopefully a lot of the data cleaning and study setup that is done now sounds similar to a set of future scientists who use AI tools to operate and check these basic programatic and statistical tasks.
- zozbot234 2y agoI really really hope it doesn't. The last thing I ever want is to be living in a world where all the scientific studies are written by hallucinating stochastic parrots.
- latexr 2y agohttps://archive.ph/20250307115346/https://www.nature.com/articles/d41586-025-00648-5 https://archive.ph/20250307115346/https://www.nature.com/art...
- sega_sai 2y agoAs a researcher I say it is a good thing. Provided it gives a small number of errors that are easy to check, it is a no-brainer. I would say it is more valuable for authors though to spot obvious issues. I don't think it will drastically change the research, but is an improvement over a spell check or running grammarly.
- simonw 2y ago"YesNoError is planning to let holders of its cryptocurrency dictate which papers get scrutinized first." Sigh.
- brookst 2y agoWhy sigh? This sounds like shareholders setting corporate direction.
- weebull 2y agoExactly. That's why sigh.
- jancsika 2y agoOh wow, you've got 10,000 HN points and you are asking why someone would sigh upon seeing that some technical tool has a close association with a cryptocurrency. Even people working reputable mom-and-pops retail jobs know the reputation of retail due to very real high-pressure sales techniques (esp. at car dealerships). Those techniques are undeniably "sigh-able," and reputable retail shops spend a lot of time and energy to distinguish themselves to their potential customers and distance themselves from that ick. Crypto also has an ick from its rich history of scams. I feel silly even explicitly writing that they have a history rich in scams because everyone on HN knows this. I could at least understand (though not agree) if you raised a question due to your knowledge of a specific cryptocurrency. But "Why sigh" for general crypto tie-in? I feel compelled to quote Tim and Eric: "Do you live in a hole, or boat?" Edit: clarification
- loufe 2y agoApart from the actual meat of the discussion, which is whether the GP's sigh is actually warranted, it's just frustrating to see everyone engage in such shallow expression. The one word comment could charitably be interpreted as thoughtful, in the sense that a lot of readers would take the time to understand their view-point, but I still think it should be discouraged as they could take some time to explain their thoughts more clearly. There shouldn't need to be a discussion on what they intended to convey. That said, your "you're that experienced here and you didn't understand that" line really cheapens the quality of discourse here, too. It certainly doesn't live up to the HN guidelines (https://news.ycombinator.com/newsguidelines.html https://news.ycombinator.com/newsguidelines.html). You don't have to demean parent's question to deconstruct and disagree with it.
- yosito 2y agoWhile I don't doubt that AI tools can spot some errors that would be tedious for humans to look for, they are also responsible for far more errors. That's why proper understanding and application of AI is important.
- tomrod 2y agoI know academics that use it to make sure their arguments are grounded, after a meaningful draft. This helps them in more clearly laying out their arguments, and IMO is no worse than the companies that used motivated graduate students for review the grammar and coherency of papers written by non-native language speakers.
- webdoodle 2y agoThe push for AI is about controlling the narrative. By giving AI the editorial review process, it can control the direction of science, media and policy. Effectively controlling the course of human evolution. On the other hand, I'm fully supportive of going through ALL of the rejected scientific papers to look for editorial bias, censorship, propaganda, etc.
- TZubiri 2y agoIt's fine, since it's not really just AI, it's the crypto hackers in charge of the AI. As it stands there's always a company (juristic person) behind AIs, I haven't yet seen an independent AI.
- nathan_compton 2y agoOne thing about this is that these kinds of power struggles/jostlings are part of every single thing humans do at almost all times. There is no silver bullet that will extricate human beings from the condition of being human, only constant vigilance against the ever changing landscape of who is manipulating and how.
- bookofjoe 2y agohttps://archive.ph/fqAig https://archive.ph/fqAig
- TZubiri 2y agoDidn't this YesNoError thing start as a memecoin?
- huijzer 2y agoI think improving incentives is the real problem in science. Tools aren’t gonna fix it.
- gusgus01 2y agoI'm extremely skeptical for the value in this. I've already seen wasted hours responding to baseless claims that are lent credence by AI "reviews" of open source codebases. The claims would have happened before but these text generators know how to hallucinate in the correct verbiage to convince lay people and amateurs and are more annoying to deal with.
- RainyDayTmrw 2y agoPerhaps our collective memories are too short? Did we forget what curl just went through with AI confabulated bug reports[1]? [1]: https://daniel.haxx.se/blog/2024/01/02/the-i-in-llm-stands-for-intelligence/ https://daniel.haxx.se/blog/2024/01/02/the-i-in-llm-stands-f...
- InkCanon 2y agoThis sounds way, way out of how LLMs work. They can't count the R's in strarwberrrrrry, but they can cross reference multiple tables of data? Is there something else going on here?
- Groxx 2y agoAccurately check: lol no chance at all, completely agreed. Detect deviations from common patterns, which are often pointed out via common patterns of review feedback on things, which might indicate a mistake: actually I think that fits moderately well. Are they accurate enough to use in bulk? .... given their accuracy with code bugs, I'm inclined to say "probably not", except by people already knowledgeable in the content. They can generally reject false positives without a lot of effort.
- lfsh 2y agoI am using Jetbrain's AI to do code analysis (find errors). While it sometimes spot something I missed it also gives a lot of confident 'advise' that is just wrong or not useful. Current AI tools are still sophisticated search engines. They cannot reason or think. So while I think it could spot some errors in research papers I am still very sceptical that it is useful as trusted source.
- _tom_ 2y agoThis basically turns research papers as a whole into a big generative adversarial network.
- sfink 2y agoDon't forget that this is driven by present-day AI. Which means people will assume that it's checking for fraud and incorrect logic, when actually it's checking for self-consistency and consistency with training data. So it should be great for typos, misleading phrasing, and cross-checking facts and diagrams, but I would expect it to do little for manufactured data, plausible but incorrect conclusions, and garden variety bullshit (claiming X because Y, when Y only implies X because you have a reasonable-sounding argument that it ought to). Not all of that is out of reach. Making the AI evaluate a paper in the context of a cluster of related papers might enable spotting some "too good to be true" things. Hey, here's an idea: use AI for mapping out the influence of papers that were later retracted (whether for fraud or error, it doesn't matter). Not just via citation, but have it try to identify the no longer supported conclusions from a retracted paper, and see where they show up in downstream papers. (Cheap "downstream" is when a paper or a paper in a family of papers by the same team ever cited the upstream paper, even in preprints. More expensive downstream is doing it without citations.)
- ForTheKidz 2y ago> people will assume that it's checking for fraud and incorrect logic, when actually it's checking for self-consistency and consistency with training data. TBF, this also applies to all humans.
- Groxx 2y agoThere is a clear difference in capability even though they share many failures
- nxobject 2y agoTo be fair, at least humans get to have collaborators from multiple perspectives and skillsets; a lot of the discussion about AI in research has assumed that a research team is one hive mind, when the best collaborations aren’t.
- lucianbr 2y agoNo, no it does not. Are you actually claiming with a straight face that not a single human can check for fraud or incorrect logic? Let's just claim any absurd thing in defense of the AI hype now.
- BurningFrog 2y agoIn the not so far future we should have AIs that have read all the papers and other info in a field. They can then review any new paper as well as answering any questions in the field. This then becomes the first sanity check for any paper author. This should save a lot of time and effort, improve the quality of papers, and root out at least some fraud. Don't worry, many problems will remain :)
- surferbayarea 2y agoHere are 2 examples from the Black Spatula project where we were able to detect major errors: - https://github.com/The-Black-Spatula-Project/black-spatula-project/issues/3 https://github.com/The-Black-Spatula-Project/black-spatula-p... - https://github.com/The-Black-Spatula-Project/black-spatula-project/issues/10 https://github.com/The-Black-Spatula-Project/black-spatula-p... Some things to note : this didn't even require a complex multi-agent pipeline. A single shot prompting was able to detect these errors.
- fph 2y agoThis black spatula case was pretty famous and was all over the internet. Is it possible that the AI is merely detecting something that was already in its training data?
- surferbayarea 2y agoThis is the original work that detected the problem.
- fph 2y agoI found many sources on the internet that state that the error in the black spatula paper was discovered by John Schwarcz of McGill University while reviewing a research paper: [1] https://www.expatgo.com/my/2024/12/15/an-error-in-arithmetic-may-have-sent-thousands-of-black-plastic-utensils-into-the-trash/ https://www.expatgo.com/my/2024/12/15/an-error-in-arithmetic... [2] https://gizmodo.com/embarrassing-math-error-scared-the-pants-off-people-over-toxic-black-kitchenware-2000540158 https://gizmodo.com/embarrassing-math-error-scared-the-pants... Is John Schwarcz behind this Yesnoerror or the black spatula project?
- systemstops 2y agoWhen people starting building tools like this to analyze media coverage of historic events, it will be a game changer.
- jongjong 2y agoI expect that for truly innovative research, it might flag the innovative parts of the paper as a mistake if they're not fully elaborated upon... E.g. if the author assumed that the reader possesses certain niche knowledge. With software design, I find many mistakes in AI where it says things that are incorrect because it parrots common blanket statements and ideologies without actually checking if the statement applies in this case by looking at it from first principles... Once you take the discussion down to first principles, it quickly acknowledges its mistake but you had to have this deep insight in order to take it there... Some person who is trying to learn from AI would not get this insight from AI; instead they would be taught a dumbed-down, cartoonish, wordcel version of reality.
- delusional 2y agoReality check: yesnoerror, the only part of the article that actually seems to involve any published AI reviewer comments, is just checking arxiv papers. Their website claims that they "uncover errors, inconsistencies, and flawed methods that human reviewers missed." but arxiv is of course famously NOT a peer-reviewed journal. At best they are finding "errors, inconsistencies, and flawed methods" in papers that human reviewers haven't looked at. Let's then try and see if we can uncover any "errors, inconsistencies, and flawed methods" on their website. The "status" is pure madeup garbage. There's no network traffic related to it that would actually allow it to show a real status. The "RECENT ERROR DETECTIONS" lists a single paper from today, but looking at the queue when you click "submit a paper" lists the last completed paper as the 21st of February. The front page tells us that it found some math issue in a paper titled "Waste tea as absorbent for removal of heavy metal present in contaminated water" but if we navigate to that paper[1] the math error suddenly disappears. Most of the comments are also worthless, talking about minor typographical issues or misspellings that do not matter, but of course they still categorize that as an "error". It's the same garbage as every time with crypto people. [1]: https://yesnoerror.com/doc/82cd4ea5-4e33-48e1-b517-5ea3e2c5f268 https://yesnoerror.com/doc/82cd4ea5-4e33-48e1-b517-5ea3e2c5f...
- EigenLord 2y agoThe role of LLMs in research is an ongoing, well, research topic of interest of mine. I think it's fine so long as a 1. a pair of human eyes has validated any of the generated outputs and 2. The "ownership rule": the human researcher is prepared to defend and own anything the AI model does on their behalf, implying that they have digested and understood it as well as anything else they may have read or produced in the course of conducting their research. Rule #2 avoids this notion of crypto-plagiarism. If you prompted for a certain output, your thought in a manner of speaking was the cause of that output. If you agree with it, you should be able to use it. In this case, using AI to fact check is kind of ironic, considering their hallucination issues. However infallibility is the mark of omniscience; it's pretty unreasonable to expect these models to be flawless. They can still play a supplementary role to the review process, a second line of defense for peer-reviewers.
- robwwilliams 2y agoGreat start but definitely will require supervision by experts in the fields. I routinely use Claude 3.7 to flag errors in my submissions. Here is a prompt I used yesterday: “This is a paper we are planning to submit to Nature Neuroscience. Please generate a numbered list of significant errors with text tags I can use to find the errors and make corrections.” It gave me a list of 12 errors of which Claude labeled three as “inconsistencies”, “methods discrepancies”. and “contradictions”. When I requested that Claude reconsider it said “You are right, I apologize” in each of these three instances. Nonetheless it was still a big win for me and caught a lot of my dummheits. Claude 3.7 running in standard mode does not use its context window very effectively. I suppose I could have demanded that Claude “internally review (wait: think again)” for each serious error it initially thought it had encountered. I’ll try that next time. Exposure of chain of thought would help.
- lifeisstillgood 2y agoIt’s a nice idea, and I would love to be able to use it for my own company reports (spotting my obvious errors before sending them to my bosses boss) But the first thing I noticed was the two approaches highlighted - one a small scale approach that does not publish first but approaches the authors privately - and the other publishes first, does not have human review and has its own cryptocurrency I don’t think anything quite speaks more about the current state of the world and the choices in our political space
- ysofunny 2y agotop two links at this moment are: > AI tools are spotting errors in research papers: inside a growing movement (nature.com) and > Kill your Feeds – Stop letting algorithms dictate what you think (usher.dev) so we shouldn't let the feed algorithms influence our thoughs, but also, AI tools need to tell us when we're wrong
- forum-soon-yuck 2y ago[dead]
- TheRealPomax 2y agoOh look, an actual use case for AI. Very nice.
- mac-mc 2y agoNow they need to do it for their own outputs to spot their own hallucination errors.
- rosstex 2y agoWhy not just skip the human and have AI write, evaluate and submit the papers?
- gosub100 2y agoWhy not skip the AI and remove "referees" that allow papers to be published that contain egregious errors?
- YeGoblynQueenne 2y agoNeeds more work. >> Right now, the YesNoError website contains many false positives, says Nick Brown, a researcher in scientific integrity at Linnaeus University. Among 40 papers flagged as having issues, he found 14 false positives (for example, the model stating that a figure referred to in the text did not appear in the paper, when it did). “The vast majority of the problems they’re finding appear to be writing issues,” and a lot of the detections are wrong, he says. >> Brown is wary that the effort will create a flood for the scientific community to clear up, as well fuss about minor errors such as typos, many of which should be spotted during peer review (both projects largely look at papers in preprint repositories). Unless the technology drastically improves, “this is going to generate huge amounts of work for no obvious benefit”, says Brown. “It strikes me as extraordinarily naive.”
- dadadad100 2y agoMuch like scanning tools looking for CVEs. There are thousands of devs right this moment chasing alleged vulns. It is early days for all of these tools. Giving papers a look over is an unqualified good as it is for code. I like the approach of keeping it private until the researcher can respond.
- Lerc 2y agoThere are two different projects being discussed here. One Open source effort and one "AI Entrepreneur" effort. YesNoError is the latter project. AI, like Cryptocurrencies faces a lot of criticism because of the snake oil and varying levels of poor applications ranging from the fanciful to outright fraud. It bothers me a bit how much of that critique spreads onto the field as well. The origin of the phrase "snake oil" comes from a touted medical treatment, a field that has charlatans deceiving people to this day. In years past I would have thought it a given that people would not consider a wholesale rejection of healthcare as a field because of the presence of fraud. Post pandemic, with the abundance of conspiracies, I have some doubts. I guess the point I'm making is judge each thing on their individual merits. It might not all be bathwater.
- LiamPowell 2y ago> for example, the model stating that a figure referred to in the text did not appear in the paper, when it did This shouldn't even be possible for most journals where cross-references with links are required as LaTeX or similar will emit an error.
- timoth3y 2y agoPerhaps this is a naive question from a non-academic, but why isn't deliberately falsifying data or using AI tools or photoshop to create images career-ending? Wouldn't a more direct system be one in which journals refused submissions if one of the authors had committed deliberate fraud in a previous paper?
- dbg31415 2y agoCan we get it to fact check politicians and Facebook now?
- tibbar 2y agoRecently I used one of the reasoning models to analyze 1,000 functions in a very well-known open source codebase. It flagged 44 problems, which I manually triaged. Of the 44 problems, about half seemed potentially reasonable. I investigated several of these seriously and found one that seemed to have merit and a simple fix. This was, in turn, accepted as a bugfix and committed to all supported releases of $TOOL. All in all, I probably put in 10 hours of work, I found a bug that was about 10 years old, and the open-source community had to deal with only the final, useful report.
- luxuryballs 2y agoThis is going to be amazing for validation and debugging one day, imagine having the fix PR get opened by the system for you with code to review including unit test to reproduce/fix the bug that caused the prod exception @.@
- FilosofumRex 2y agoThe low hanging fruit is to target papers cited in corporate media; NYT, WSJ, WPO, BBC, FT, The Economist, etc. Those papers are planted by politically motivated interlocutors and timed to affect political events like elections or appointments. Especially those papers cited or promoted by well-known propagandists like Freedman of NYT, Eric Schmidt of Google or anyone on the take of George Soros' grants.
- sunami-ai 2y agoI built this AI tool to spot "bugs" in legal agreements, which is harder than spotting errors in research papers because the law is open textured and self contradicting in many places. But no one seems to care about it on HN, Gladly, our early trial customers are really blown away by it. Video demo with human wife narrating it: https://www.youtube.com/watch?v=346pDfOYx0I https://www.youtube.com/watch?v=346pDfOYx0I Cloudflare-fronted Live site (hopefully that means it can withstand traffi): https://labs.sunami.ai/feed https://labs.sunami.ai/feed Free Account Prezi Pitch: https://prezi.com/view/g2CZCqnn56NAKKbyO3P5/ https://prezi.com/view/g2CZCqnn56NAKKbyO3P5/
- soared 2y ago> human wife
- throwup238 2y agoThat’s a subtle way of implying she isn’t a lawyer :)
- sunami-ai 2y agoShe is a hardcore human. Lawyers are not all bad, as I'm finding out. We met some amazing human lawyers on our journey so far.
- bigbuppo 2y agoI guess the AI doesn't like the competition?
- gscott 2y agoSpelling errors could be used as a gauge that your work was not produced by AI
- randomNumber7 2y agoMaybe one day AI can tell us the difference between correlation and a causal relationship.
- SwtCyber 2y agoThis is both exciting and a little terrifying. The idea of AI acting as a "first-pass filter" for spotting errors in research papers seems like an obvious win. But the risk of false positives and potential reputational damage is real...
- noiv 2y agoI'm no member of the scientific community but I fear this project or another will go beyond math errors and eventually establish some kind of incontrovertible AI entity giving a go/nogo on papers. Ending all science in the process because publishers will love it.
- deleted 2y ago[deleted]
- Rzor 2y agoThis could easily turn into a witch hunt [0], especially given how problematic certain fields have been, but I can't shake the feeling that it is still an interesting application and like the top comment said a step in the right direction. [0] - Imagine a public ranking system for institutions or specific individuals who have been flagged by a system like this, no verification or human in the loop, just a "shit list"
- Hilift 2y agoIf anyone is not aware of Retraction Watch, their implementations of "tortured phrases" was a revelation. And it has exposed some serious flaws. Like "vegetative electron microscopy". Some of the offending publications/authors have hundreds of papers. https://retractionwatch.com/2025/02/10/vegetative-electron-microscopy-fingerprint-paper-mill/ https://retractionwatch.com/2025/02/10/vegetative-electron-m... https://retractionwatch.com/2024/11/11/all-the-red-flags-scientific-reports-retracts-paper-sleuths-called-out-in-open-letter/ https://retractionwatch.com/2024/11/11/all-the-red-flags-sci...
- seventytwo 2y agoThis is a fantastic use of AI.
- nhlx2 2y agoHas AI been used to find errors in Knuth’s books? Or Chomsky’s?
- hackburg 2y ago[dead]
- thdhhghgbhy 2y agoNow all AI tools have to do is spot errors made by themselves.
- anonu 2y agoWait, I threw out my black plastic spatula for nothing? So there was all this media noise about it - but not a single article came across my (many) newsfeeds about a mistake or a retraction.
- Nickolya 2y agoAI tools revolutionizing research by spotting errors is a game-changer for academia. With the ability to detect inconsistencies, plagiarism, and even fabricated data, AI is enhancing the credibility of scientific studies. This is especially crucial in a time when the volume of published research is growing exponentially, making manual fact-checking nearly impossible. However, despite the benefits, AI-driven tools are facing increasing restrictions. Many schools and universities, as well as some governments, have started blocking access to AI services, fearing academic dishonesty or misuse. If you still need access to these tools for legitimate research purposes, proxy services like NodeMaven can help bypass these restrictions, ensuring you stay connected to the latest advancements. I can drop you a link, it helped me a lot while writing my thesis.: https://nodemaven.com/ https://nodemaven.com/