RE: https://mathstodon.xyz/@highergeometer/115725799575506491
From now on, my procedure to check papers that are suspicious of being made with AI includes using the search function of my PDF reader and trying to find “**”, and maybe also “__”.
There might be some false positives in papers about programming languages.
"Science is characterized by collaboration and cooperation, but also by uncertainty, competition, and inequality. While there has always been some concern that these pressures may compel some to defect from the scientific research ethos—i.e., fail to make genuine contributions to the production of knowledge or to the training of an expert workforce—the focus has largely been on the actions of lone individuals. Recently, however, reports of coordinated scientific fraud activities have increased. Some suggest that the ease of communication provided by the internet and open-access publishing have created the conditions for the emergence of entities—paper mills (i.e., sellers of mass-produced low quality and fabricated research), brokers (i.e., conduits between producers and publishers of fraudulent research), predatory journals, who do not conduct any quality controls on submissions—that facilitate systematic scientific fraud. Here, we demonstrate through case studies that i) individuals have cooperated to publish papers that were eventually retracted in a number of journals, ii) brokers have enabled publication in targeted journals at scale, and iii), within a field of science, not all subfields are equally targeted for scientific fraud. Our results reveal some of the strategies that enable the entities promoting scientific fraud to evade interventions. Our final analysis suggests that this ability to evade interventions is enabling the number of fraudulent publications to grow at a rate far outpacing that of legitimate science."
> Docampo, Abalkina, and others say there’s little in the new paper that wasn’t already strongly suspected. But the dramatic confirmation that the study offers may shift the needle, they say. “We’re massively behind the curve on making visible and realizing the extent of the problem,” Kaltenbrunner says. “The sheer scale of it is the takeaway message here.”
https://www.science.org/content/article/scientific-fraud-has-become-industry-alarming-analysis-finds
Eliezer Masliah: Long Shadow of Fraud in Alzheimer’s Research
https://archive.is/URjfk
https://news.ycombinator.com/item?id=42910829
https://en.wikipedia.org/wiki/Charles_Piller
Forthcoming book: https://archive.is/cQRgK
Scores of papers by Eliezer Masliah, prominent neuroscientist and top NIH official, fall under suspicion
https://archive.is/zosG4#selection-1228.0-1228.1
https://en.wikipedia.org/wiki/Eliezer_Masliah
https://www.science.org/content/article/research-misconduct-finding-neuroscientist-eliezer-masliah-papers-under-suspicion
#disease #Alzheimers #fraud #ScientificFraud #AcademicFraud #EliezerMasliah
The Francesca Gino case ended with her being found guilty of data manipulation, exposed as a serial plagiarist, and losing her defamation suit against the Data Colada bloggers.
Here's a very watchable 15-minute summary by Pete Judo: https://m.youtube.com/watch?si=DW5gVlr364Nzb4ta&v=Q9tgyVPytBk
#ResearchIntegrity #FrancescaGino #ScientificFraud #HarvardUniversity #Plagiarism #DataColada
#AI #GenerativeAI #ScientificFraud #ChatGPT #ChatBots #AcademicPublishing: "We searched and scraped Google Scholar using the Python library Scholarly (Cholewiak et al., 2023) for papers that included specific phrases known to be common responses from ChatGPT and similar applications with the same underlying model (GPT3.5 or GPT4): “as of my last knowledge update” and/or “I don’t have access to real-time data” (see Appendix A). This facilitated the identification of papers that likely used generative AI to produce text, resulting in 227 retrieved papers. The papers’ bibliographic information was automatically added to a spreadsheet and downloaded into Zotero.
We employed multiple coding (Barbour, 2001) to classify the papers based on their content. First, we jointly assessed whether the paper was suspected of fraudulent use of ChatGPT (or similar) based on how the text was integrated into the papers and whether the paper was presented as original research output or the AI tool’s role was acknowledged. Second, in analyzing the content of the papers, we continued the multiple coding by classifying the fraudulent papers into four categories identified during an initial round of analysis—health, environment, computing, and others—and then determining which subjects were most affected by this issue (see Table 1). Out of the 227 retrieved papers, 88 papers were written with legitimate and/or declared use of GPTs (i.e., false positives, which were excluded from further analysis), and 139 papers were written with undeclared and/or fraudulent use (i.e., true positives, which were included in further analysis). The multiple coding was conducted jointly by all authors of the present article, who collaboratively coded and cross-checked each other’s interpretation of the data simultaneously in a shared spreadsheet file."
Academic journals, archives, and repositories are seeing an increasing number of questionable research papers clearly produced using generative AI. They are often created with widely available, general-purpose AI applications, most likely ChatGPT, and mimic scientific writing. Google Scholar easily locates and lists these questionable papers alongside reputable, quality-controlled research. Our analysis of a selection of
GPT-fabricated scientific papers on Google Scholar: Features, spread, implications
https://misinforeview.hks.harvard.edu/article/gpt-fabricated-scientific-papers-on-google-scholar-key-features-spread-and-implications-for-preempting-evidence-manipulation
https://news.ycombinator.com/item?id=41477516
* many about applied, controversial topics susceptible to disinformation
* environment, health, computing
* resulting potential for malicious manipulation of society’s evidence base, particularly in politically divisive domains, a concern
#AcademicJournals #ScientificLiterature #FakeScience #GPT #LLM #disinformation #ScientificFraud #GoogleScholar #PostTruth
Academic journals, archives, and repositories are seeing an increasing number of questionable research papers clearly produced using generative AI. They are often created with widely available, general-purpose AI applications, most likely ChatGPT, and mimic scientific writing. Google Scholar easily locates and lists these questionable papers alongside reputable, quality-controlled research. Our analysis of a selection of
Many fraudulent scientific papers contain "tortured phrases," standard scientific terms paraphrased into gibberish. Breast cancer is a scary disease, but what is bosom peril? These phrases are likely popping up because scientists, to boost their article count, are running texts through paraphrasing software, which helps them avoid plagiarism accusations. And new AI technologies may be crafting some article text from whole cloth.
I really enjoyed speaking on the ICSSI conference panel (icssi.org) on junk, fraud, retractions, and paper mills; we got lots of great questions and could have kept going all morning! Thanks to Daniel Larremore for the invite and especially Daniel Acuna for organising and chairing.
🧵
#PaperMills #ICSSI #ScienceofScience #PublicationEthics #JournalPublication #ScientificFraud #AcademicPublishing #Retractions
Markus Redeker
Doug Bostrom
Paul Melis
Victoria Stuart 🇨🇦 🏳️⚧️
Matt Hodgkinson
Miguel Afonso Caetano
Radiojane
Paul Guinnessy