{"id":"W4412800187","doi":"10.23974/ijol.2025.vol10.2.419","title":"AI in Scholarly Publishing","year":2025,"lang":"en","type":"article","venue":"International Journal of Librarianship","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Publishing; Library science; Scholarly communication; Computer science; Data science; History; Political science; Law","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":[],"consensus_categories":[],"category_scores_codex":[0.0007102982,0.00005929404,0.0001437792,0.0008302779,0.00002220675,0.0009111274,0.0003427591,0.0001069158,0.0001402414],"category_scores_gemma":[0.002541388,0.00005291681,0.00007746984,0.0003480495,0.00002528302,0.005778524,0.00003164211,0.0007031386,0.00001175714],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001792336,"about_ca_system_score_gemma":0.001032403,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001246583,"about_ca_topic_score_gemma":0.00002134805,"domain_scores_codex":[0.9987342,0.0000556815,0.0006341322,0.00008651818,0.0003760593,0.0001133668],"domain_scores_gemma":[0.9985035,0.0002096397,0.000161224,0.00009103402,0.000950952,0.00008364302],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007044129,0.000268704,0.7293227,0.00003354451,0.0001150339,0.0002231621,0.001070626,0.00002633338,0.00103446,0.04742214,0.02765435,0.1921245],"study_design_scores_gemma":[0.0007629621,0.0002573699,0.6871825,0.002246338,0.00004982042,0.0003802526,0.003133639,0.0004196637,0.01658111,0.1812965,0.1075282,0.0001615498],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5598415,0.0007052074,0.002847602,0.407293,0.004949267,0.0001098021,0.00000168196,0.00001502286,0.02423695],"genre_scores_gemma":[0.9814028,0.00006108486,0.000992925,0.01595086,0.0008482417,0.000001865558,0.000005223016,0.000005611198,0.000731438],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4215613,"threshold_uncertainty_score":0.8786023,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1644525539803082,"score_gpt":0.4481998796548292,"score_spread":0.283747325674521,"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."}}