Last verified: 16 August 2026.
A rising share of retractions traced to organized fraud rather than individual error share two tell-tale signatures: manuscripts produced by paper mills, and prose containing tortured phrases — synonym-mangled versions of standard terminology that betray machine-paraphrased or disguised-plagiarized text. Neither signal proves misconduct on its own, but together they are now central to how publishers and institutions triage suspect submissions before they ever reach peer review.
This guide covers what a paper mill actually sells, why demand for that product exists in the first place, how editors and integrity offices detect it (tortured phrases among several other signals, laid out in a table below), what the publishing industry’s two main coordinated responses (the STM Integrity Hub and COPE’s 2025 retraction guidelines) actually do, the scale of the retraction waves that have resulted, and what an institution should do if a paper mill purchase is alleged against one of its own researchers.
What a paper mill is, and what it actually sells
CASRAI’s Dictionary defines a paper mill as a commercial operation that produces fabricated or low-effort manuscripts and sells authorship slots, or that brokers acceptance of such manuscripts into journals. The defining feature isn’t poor writing quality — it’s the commercial, for-profit production of research outputs designed to look like real science without an underlying real study. A mill’s product line typically includes some combination of:
- Authorship for sale. Slots on an already-written or already-accepted manuscript offered to buyers who had no role in the underlying work, priced by author position (first vs. middle author) and by the target journal’s prestige, sometimes advertised openly on social media or via brokers and closed-membership groups.
- Wholly fabricated manuscripts. Papers with no underlying study at all, built from templated structure, plausible-looking (often reused or subtly altered) figures, and statistical tables generated or copied rather than derived from real data.
- Templated manuscripts. Batches of papers that share an identical structural skeleton — the same figure layout, the same statistical tables, the same discussion-section phrasing — with only the gene name, disease, chemical compound, or dataset swapped out.
- Reused or recycled images. Figures — particularly Western blots and flow cytometry plots in biomedical literature — reappearing, sometimes digitally altered, across manuscripts submitted to different journals under different author names.
- Compromised or fake peer review. Fabricated reviewer identities, or reviewer-suggestion systems gamed so a paper mill effectively reviews its own submission — a mechanism documented as a specific, exploited weakness in some journals’ peer-review workflows.
- Citation rings. Coordinated cross-citation among a mill’s own output, or brokered citations sold separately from authorship, to inflate a paper’s or an author’s apparent influence; see citation cartels for the closely related pattern among legitimate-looking author and journal groups.
COPE and STM’s joint 2022 research report (conducted with Maverick Publishing Services, based on real publisher-submitted data) was the first industry-wide attempt to size the problem using shared data rather than any single publisher’s anecdotal experience, and it concluded the scale required coordinated, cross-publisher action rather than each journal fighting it alone — the direct origin of the United2Act initiative covered below.
Not every low-quality or templated-looking manuscript is paper mill output. Legitimate contract research organizations, professional medical-writing services operating under recognized authorship guidelines (e.g. GPP 2022 for industry-sponsored publications), and English-language editing services that improve a manuscript without altering its scientific content are not paper mills — the distinguishing question is whether the underlying research and the claimed authorship contributions are real.
Why the market exists: the demand side
A paper mill has no customers without demand, and the demand is structural, not incidental. Publication-count requirements tied to career milestones — promotion and tenure decisions, medical residency or specialty-board completion, doctoral graduation, and, in some health systems, direct financial bonuses for publishing in journals above a given impact factor — create a market for a fast, guaranteed way to add a line to a CV. COPE and STM’s 2022 research and subsequent industry commentary have specifically identified rigid publication quotas, rather than any single country or discipline, as the underlying demand driver: wherever a system counts publications as a proxy for competence without independently verifying the work behind them, a market for counterfeit publications can form to meet that count. Several national research-evaluation and health-system authorities have since moved to reduce or eliminate blunt publication-count and bonus-based evaluation criteria specifically in response to this dynamic, alongside broader responsible-metrics efforts such as DORA and CoARA.
This context matters for how institutions should think about culpability, and CASRAI states it plainly: buying or selling authorship is research misconduct, full stop, and the researcher who does it is responsible for that choice. But a researcher operating inside a system that makes career survival contingent on a publication count they cannot otherwise reach is also, in a real sense, a product of the incentive structure that created the market — the two things are both true at once, and treating them as mutually exclusive gets the ethics and the policy response wrong in different ways. Naming coercive or badly-designed evaluation systems as a contributing cause is not an excuse for an individual’s conduct, and CASRAI does not present it as one; it is, however, the reason serious institutional and funder-level responses (see United2Act below) treat evaluation-system reform as part of the fix, not just faster manuscript screening.
Tortured phrases as a detection signal
A tortured phrase is an unusual paraphrase of established technical terminology, produced by automated synonym substitution, that a domain expert immediately recognizes as a corrupted version of a standard term. The concept and term were introduced by Guillaume Cabanac (Universite de Toulouse), Cyril Labbe (Universite Grenoble Alpes), and Alexander Magazinov in their 2021 paper “Tortured phrases: A dubious writing style emerging in science” (arXiv:2107.06751), which documented the pattern across established journals and was covered by Nature the same year.
The mechanism is straightforward: paraphrasing software — used either to evade plagiarism-detection tools by substituting synonyms for lifted text, or to disguise machine-translated or AI-generated text as original writing — has no domain knowledge, so it substitutes synonyms for fixed technical terms that should never be paraphrased. The result is text that reads as plausible English at a glance but is instantly recognizable as wrong to anyone who knows the field. Documented, widely-cited examples include:
- “counterfeit consciousness” for artificial intelligence
- “profound learning” for deep learning
- “colossal information” for big data
- “cruel temperature” for mean temperature
- “irregular esteem” for random value
Cabanac and colleagues built the Problematic Paper Screener, a public tool that queries a database of tens of millions of indexed articles against a list of thousands of known tortured phrases to flag papers for post-publication reassessment — the same underlying detection logic several commercial and publisher-run screening tools now license or replicate at submission time, before publication rather than after.
Two caveats matter for anyone using this as a signal rather than a definition. First, a tortured phrase is evidence of paraphrasing-tool use, not proof of fabricated results on its own — genuinely real research can, in principle, be reported using tortured phrasing if an author (or an editing vendor working for them) ran the text through the wrong kind of tool. Second, genuinely new terminology introduced in good faith by an emerging subfield, properly defined at first use and applied consistently thereafter, is not tortured phrasing — the tell is a term that reads as a corrupted synonym for something that already has an established name, not an unfamiliar but internally consistent new one.
Detection signals at a glance
No single signal below is, by itself, proof of paper mill involvement — editors and integrity offices look for more than one appearing together before treating a submission or a published paper as a serious concern. This table summarizes the main ones and how each is typically caught.
| Signal | What it looks like | How it’s typically detected |
|---|---|---|
| Tortured phrases | Standard technical terms replaced with odd synonyms (e.g. “counterfeit consciousness” for artificial intelligence) | Automated phrase-list screening, e.g. the Problematic Paper Screener and STM Integrity Hub-connected tools |
| Template reuse | Batches of papers sharing identical structure, figure layout, and statistical tables with only a keyword swapped | Cross-manuscript similarity and structural-pattern analysis at submission |
| Image duplication or manipulation | The same or a digitally altered Western blot, flow-cytometry plot, or other figure appears across unrelated manuscripts | Tools such as Clear Skies’ Papermill Alarm and dedicated image-forensics screening; see image manipulation |
| Implausible authorship changes | Author lists that change substantially, or add unrelated authors, late in the review or production process | Editorial-office review of authorship-change requests against journal policy |
| Suspicious reviewer suggestions | Author-suggested reviewers whose contact details route back to the author or a broker rather than an independent researcher | Editor verification of reviewer identity and institutional affiliation before invitation |
| Submission-pattern clustering | Statistically anomalous spikes in submissions from a single institution, region, or topic that don’t match that group’s known publication history | Cross-publisher submission-metadata analysis (shared IP addresses, disposable-looking author email domains, unusual co-authorship networks) |
| Citation-ring activity | Coordinated, disproportionate cross-citation among a cluster of papers or authors | Citation-pattern analysis; see citation cartels |
| Compromised peer review | Reviews that arrive unusually fast, are generic, or effectively originate from the submitting party | Editorial scrutiny of review turnaround time and content quality, cross-checked against reviewer identity |
Why the two signals travel together
Paper mills and tortured phrases are not the same thing, but they correlate for a structural reason: a mill producing large volumes of templated manuscripts across many buyers has a strong incentive to make each output look textually distinct enough to survive plagiarism-similarity checks like Turnitin or iThenticate, which compare submitted text against prior published text. Running a shared template through automated paraphrasing software is a cheap way to generate many surface-distinct versions of the same underlying boilerplate — which is exactly the kind of text tortured-phrase detectors are built to catch. That’s why STM Integrity Hub-connected tools and several individual publisher pipelines now run tortured-phrase screening as one signal alongside citation-pattern analysis, reused-image detection, and submission-metadata checks rather than relying on any single indicator.
Neither signal is used in isolation to reject or retract a paper. COPE’s own case guidance and the flowchart-based decision process described in CASRAI’s COPE flowcharts guide treat a tortured-phrase hit or a templated-manuscript pattern as grounds to investigate, not as automatic proof of misconduct — editors are expected to look at the pattern in context (does the paper also show recycled figures, an implausible submission-to-acceptance timeline, or an author group with no verifiable institutional affiliation?) before acting.
Other red flags editors and integrity offices watch alongside these
Paper mill and tortured-phrase detection is usually one part of a broader screening pattern. Related signals not already covered in the table above:
- Fabrication and falsification of underlying data, of which paper mill output is a specific commercial variant.
- Submission via a predatory journal or a compromised guest-editor special issue — a channel paper mills have specifically been documented exploiting because peer review is weaker or effectively absent; see CASRAI’s guide on guest editor vetting.
What publishers and institutions are doing about it
The STM Integrity Hub
The STM Integrity Hub, operated by STM Solutions (the operational arm of the International Association of STM Publishers), is a shared, cloud-based screening platform that lets participating publishers check submitted manuscripts against pooled integrity signals before publication — an “early warning system” run collectively rather than by any one publisher alone, in a protected environment designed to respect data-privacy and competition-law constraints between competing publishers. It integrates a modular set of independent detection tools, including tortured-phrase screening, duplicate-submission and citation checks, reused-image detection (via tools such as Clear Skies’ Papermill Alarm), AI-generated-text detection, and cross-publisher submission-pattern analysis. As of a December 2025 report in Science Editor, roughly 40 publishers were using the Hub, screening over 125,000 papers a month and intercepting approximately 1,000 suspected paper mill submissions monthly across about 20 connected detection tools and seven editorial systems.
United2Act
United2Act is the multi-stakeholder initiative that grew directly out of the 2022 COPE/STM paper mill research: at a May 2023 summit, roughly 40 participants — publishers (including Elsevier, Springer Nature, Taylor & Francis, Wiley, and others), research institutions, funders, and infrastructure organizations (Crossref, ORCID, Clarivate, Digital Science) — agreed a consensus statement covering five areas of collaborative action: education and awareness, improving post-publication correction processes, researching paper mills, developing shared trust markers, and strengthening cross-sector communication. It is a coordination framework rather than a detection tool — its output is shared standards and practices that individual publishers and platforms (including the Integrity Hub) then implement. See CASRAI’s dedicated guide to United2Act for the full detail.
COPE’s 2025 retraction guidelines
COPE’s Committee on Publication Ethics revised its retraction guidelines in September 2025 (Version 3, replacing the 2019 version), naming paper mill involvement, compromised peer review (fake reviewers, citation manipulation), unverifiable authorship, and undisclosed AI use as explicit retraction grounds for the first time — codifying paper mill activity as a named category rather than leaving it to fall under a more general “fraud” heading. The revised guidelines also recommend crediting third parties (post-publication reviewers, “sleuths,” or readers) who raised a valid concern in the retraction notice, with their permission, and require mass-retraction notices tied to coordinated fraud to state plainly that the retraction is part of a systematic pattern rather than an isolated case. See CASRAI’s guide to how a retraction actually happens for the full editorial process these grounds feed into, and the COPE flowcharts guide for how editors work through a suspected-misconduct case step by step.
The scale of the resulting retraction waves
The clearest documented case of what large-scale paper mill cleanup looks like in practice is Hindawi, a fully open-access publisher acquired by Wiley in 2021. After pausing special-issue publishing in mid-2022 in response to identified paper-mill activity, Wiley disclosed in December 2023 that it was in the process of retracting more than 8,000 Hindawi articles tied to compromised peer review and paper-mill involvement — described at the time as more than any single publisher had previously retracted at once. By 2024, cumulative retractions across the affected titles had passed 11,000 articles; Clarivate had removed roughly 19 Hindawi journals from the Web of Science Master Journal List in March 2023, Hindawi closed four journals outright in May 2023, and Wiley discontinued the Hindawi brand name entirely in 2024, folding the surviving former-Hindawi titles into its main Wiley Online Library portfolio. This episode is the single largest publicly documented paper-mill-driven retraction event to date and is a large part of why the broader retraction rate across scholarly publishing rose sharply in 2023 — but it should be read as a concentrated event at one publisher rather than evidence that a comparable share of the literature generally is affected; independent estimates of paper-mill-linked output remain a small fraction — commonly cited as under 1% — of the literature overall.
What this means in practice for authors and research institutions
For legitimate authors and institutions, the practical takeaway isn’t defensive — none of these detection systems are designed to catch honestly reported research, including research that happens to use unfamiliar terminology or was run through a professional (non-paraphrasing) editing service. The institutional relevance is upstream of any individual manuscript:
- Research-integrity offices increasingly need to be able to explain paper mill and tortured-phrase findings to faculty and administrators when a retraction or expression-of-concern notice names an affiliated author, including cases where an author unknowingly bought into, or was added to, a paper mill product.
- Hiring, tenure, and grant-review committees relying on publication counts or citation metrics are exposed to the same fabricated-output problem — a paper mill manuscript that hasn’t yet been caught still counts toward an author’s record until it’s retracted.
- Institutions co-authoring or collaborating internationally should be aware that paper mill activity is not evenly distributed globally, and that a sudden, unexplained surge in a collaborator’s publication output is itself a signal worth a direct conversation, not an accusation.
If a paper mill purchase is alleged against your own researcher
An allegation is not a finding, and institutions have a documented process for exactly this situation rather than needing to improvise one:
- Route it through the normal misconduct-inquiry process, not an ad hoc review — see CASRAI’s guide to how a research misconduct investigation actually works for the inquiry-then-investigation structure most US institutions follow, and institutional vs. federal jurisdiction if federal funding is involved.
- Separate co-authors from the allegation’s target where the evidence supports it. A named co-author who was added to a paper mill product without knowledge of its origin is a documented, real pattern, not a hypothetical — see CASRAI’s guide on how a co-author’s misconduct retraction affects innocent collaborators.
- Use CRediT contributor statements as an investigative tool, not just a preventive one — asking a named author to describe their specific, per-role contribution under CRediT is a concrete, falsifiable question that a genuine paper-mill “author” typically cannot answer.
- Preserve the respondent’s rights throughout. See CASRAI’s guide on respondent rights during an ORI research misconduct investigation — an allegation triggers a process with defined procedural protections, not an assumption of guilt.
- Know the range of outcomes. Confirmed findings can lead to consequences up to and including a voluntary exclusion agreement or formal findings with funding and career consequences — see CASRAI’s guide to the consequences of research misconduct — but the process exists precisely so that outcome is only reached after a fair, evidence-based review.
- Protect whoever raised the concern. Many paper-mill findings originate from an internal report or an external “sleuth.” See CASRAI’s guide to whistleblower protections for reporting authorship misconduct or coercion.
Frequently asked questions
Is a tortured phrase proof that a paper is fraudulent?
No. It’s evidence that some portion of the text passed through automated paraphrasing software, which is a strong reason to investigate further — checking for other signals like recycled figures, an implausible submission history, or unverifiable authorship — but not, by itself, proof of fabricated data or a paper mill origin.
Can legitimate research accidentally trigger these detectors?
It’s possible but uncommon. A non-native-English-speaking author using an inappropriate machine-translation or paraphrasing tool (rather than a professional editing service) on an otherwise genuine manuscript could introduce tortured phrasing without any underlying misconduct. This is exactly why COPE guidance treats a detection hit as a trigger for editorial investigation, not an automatic rejection.
Who actually runs the STM Integrity Hub — is it a single company’s product?
It’s operated by STM Solutions on behalf of participating STM Association member publishers, and works by integrating multiple independent third-party and publisher-built detection tools (rather than being one proprietary detector) inside a shared, access-controlled environment.
Does using CRediT or transparent authorship statements prevent paper mill activity?
Not by itself, but it raises the cost of it: a paper mill selling authorship slots depends on contributor claims that can’t be checked. Requiring a specific, per-role CRediT statement gives editors a concrete, falsifiable claim to question if a listed author can’t describe their own contribution — one input among several, not a standalone defense.
What should an editor or institution do if they suspect a submission is paper mill output?
Follow the applicable COPE case guidance and flowchart rather than acting unilaterally — see CASRAI’s COPE flowcharts guide for the plagiarism/duplicate-submission/authorship decision trees, and the retraction process guide for what happens if the investigation confirms the concern after publication.
Why does demand for paper mill services exist in the first place?
Primarily because some evaluation systems — for academic promotion, medical residency or specialty completion, doctoral graduation, or direct financial bonuses — have historically counted publications as a proxy for competence without independently verifying the underlying work. COPE and STM’s 2022 research identified rigid publication-count requirements as the structural demand driver behind the paper mill market, which is why serious institutional responses increasingly pair faster detection with evaluation-system reform, alongside efforts such as DORA and CoARA.
Is a researcher who buys authorship also a victim of the system that pressured them?
Both things can be true without one excusing the other. Buying or selling authorship is research misconduct, and the individual who does it is accountable for that choice under the institution’s normal misconduct process. At the same time, a coercive or badly designed evaluation system that makes career survival contingent on an unreachable publication count is a documented contributing cause of demand — which is why credible sector-wide responses treat evaluation reform as part of the fix, not a substitute for individual accountability.
