{"id":"W4415752060","doi":"10.1016/j.jds.2025.10.024","title":"Fabricated citations in the age of AI: A wake-up call for editors, reviewers, and authors","year":2025,"lang":"en","type":"article","venue":"Journal of Dental Sciences","topic":"Academic Publishing and Open Access","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"MEDLINE","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0147476,0.00006421698,0.0002485034,0.0004509357,0.0002074782,0.000661485,0.002072469,0.00005879015,0.00001007624],"category_scores_gemma":[0.0106028,0.00003160875,0.00009403288,0.002203974,0.0004108401,0.001338253,0.0001092312,0.0002761061,9.122013e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002455519,"about_ca_system_score_gemma":0.0002156664,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006684834,"about_ca_topic_score_gemma":0.00007381002,"domain_scores_codex":[0.9973735,0.0002517349,0.0008274415,0.000163647,0.001237857,0.0001458862],"domain_scores_gemma":[0.9970734,0.001988341,0.0005040218,0.0001060403,0.0002780026,0.00005017134],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.00003344157,0.00006740688,0.2375485,0.00001699383,0.00001410173,0.000007877129,0.002679891,0.00006235536,0.0005128616,0.005047719,0.7304971,0.02351178],"study_design_scores_gemma":[0.001414092,0.0004864412,0.4499203,0.0007062653,0.00008718634,0.0001169847,0.03402852,0.001758697,0.0005271075,0.1373191,0.3733749,0.0002604049],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9347953,0.003577803,0.005632075,0.04423142,0.007358361,0.0004410494,0.00002157744,0.00000495779,0.003937518],"genre_scores_gemma":[0.9977015,0.00008297525,0.0006246181,0.0008385286,0.0002364896,0.000003118592,4.738584e-7,0.000001197871,0.0005111162],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3571222,"threshold_uncertainty_score":0.9977313,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09594412480757697,"score_gpt":0.463780199996447,"score_spread":0.36783607518887,"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."}}