{"id":"W4386541616","doi":"10.1002/leap.1578","title":"Risks of abuse of large language models, like <scp>ChatGPT</scp>, in scientific publishing: Authorship, predatory publishing, and paper mills","year":2023,"lang":"en","type":"article","venue":"Learned Publishing","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":87,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Thompson Rivers University","keywords":"Publishing; Mill; Scientific publishing; Key (lock); Public relations; Computer science; Political science; Law; Engineering; Computer security; Mechanical engineering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":["metaresearch","research_integrity"],"domain":"methods","study_design":"theoretical_or_conceptual","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":["metaresearch","research_integrity","scholarly_communication"],"domain":"evaluation","study_design":"theoretical_or_conceptual","genre":"commentary","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.1239591,0.0007538835,0.0009003947,0.003909383,0.00533059,0.02169803,0.00262506,0.007440561,0.01897213],"category_scores_gemma":[0.4776718,0.001128044,0.001239557,0.003966838,0.01568545,0.03092592,0.009744434,0.0102418,0.01217219],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00400908,"about_ca_system_score_gemma":0.005852243,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00121021,"about_ca_topic_score_gemma":0.001565996,"domain_scores_codex":[0.813063,0.1061059,0.0135763,0.007349502,0.05758516,0.002320097],"domain_scores_gemma":[0.2098032,0.5732266,0.05699644,0.1056671,0.04738846,0.00691806],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000714984,0.0001874487,0.0225074,0.002019098,0.0002331732,0.002292566,0.0454624,0.001795281,0.003922239,0.3556357,0.2294968,0.3357329],"study_design_scores_gemma":[0.0001288269,0.0003743408,0.005811715,0.003991557,0.0001489905,0.006714137,0.01203309,0.007535129,0.00976152,0.3307225,0.6223655,0.0004126275],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.07111169,0.01387046,0.1359092,0.5932745,0.01103163,0.0003538494,0.001396861,0.006220748,0.1668311],"genre_scores_gemma":[0.7036083,0.007243314,0.07768049,0.1092605,0.01529193,0.0006963416,0.001180127,0.006385394,0.07865364],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9925594,"threshold_uncertainty_score":0.6555664,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2084196632622204,"score_gpt":0.4104631433775228,"score_spread":0.2020434801153024,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}