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    AI Paper Mill & Research Integrity Screener

    by PubsProToolkit

    1

    First-pass screener that flags AI-generated, paper-mill, and fabricated scholarship using tortured-phrase, citation, statistical, and template detectors.

    $12

    · or 60 credits

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    About this skill

    Journals, universities, and research-integrity offices are being flooded with AI-generated and paper-mill submissions, and the available screening tools are still immature. This skill encodes the red flags that experienced integrity investigators look for and turns any compatible agent into a structured, evidence-cited first-pass screener. It runs six detector passes over a manuscript, abstract, or review report: A. Tortured phrases & lexical fingerprints — established technical terms mangled by synonym-swapping paraphrase tools (e.g., "counterfeit consciousness" for artificial intelligence). B. Citation fabrication & manipulation — hallucinated references, DOI/title mismatches, citation-content mismatches, and coercive self-citation patterns. C. Statistical & numerical impossibilities — GRIM/GRIMMER inconsistencies, impossible percentages, p-value vs test-statistic conflicts, and out-of-range effect sizes. D. Template & paper-mill fingerprints — shared skeletons with swapped topic nouns, placeholder residue, and recycled figures. E. AI-generation stylistic markers — filler scaffolding and hedged uniformity (weighted low; only counts in clusters). F. Metadata & provenance anomalies — affiliation/email mismatches, brokered-authorship language, and version churn. Every flag is reported with the exact quoted span, its location, a confidence level, and at least one innocent explanation, then aggregated into a calibrated concern level (LOW / ELEVATED / HIGH) using a convergence-based scoring rubric. The skill is deliberately built as triage, not verdict: it never asserts misconduct, never screens on author identity or nationality, and always ends with recommended next steps for a human reviewer. What's included: a lean SKILL.md orchestrator plus a bundled REFERENCE.md containing the detailed detector playbooks, the convergence-based scoring rubric, and a ready-to-fill report template. Designed for editors, peer reviewers, and research-integrity officers who need a fast, defensible, human-in-the-loop first pass before deeper investigation.

    Details

    How to install

    Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.

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    Passed automated security review

    Permissions

    Read Files
    Browser
    Network Access

    Allowed Hosts

    doi.org
    api.crossref.org

    File Scopes

    *.md
    *.pdf
    *.txt

    Read Files is needed to ingest the manuscript/abstract being screened. Browser and Network Access are optional and used only to verify DOIs and citations against public registries (e.g., Crossref, doi.org); when unavailable, the skill reports references as unverifiable rather than guessing. The skill does not write files, run shell commands, or read environment variables.

    Creator

    PubsProToolkit builds rigor-first skills for AI agents — they write your docs and content properly, then adversarially review them to catch what's wrong before it ships. The result: cleaner output and a hard quality gate in one toolkit. Built by a CMPP-certified, PhD medical writer who brings regulated-industry standards to developer docs, content, compliance, and research integrity.

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