{"id":"W4412554048","doi":"10.1080/0142159x.2025.2523468","title":"What do we become? Artificial intelligence and academic identity","year":2025,"lang":"en","type":"article","venue":"Medical Teacher","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Identity (music); Psychology; Cognitive science; Data science; Computer science; Philosophy; Aesthetics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","sts"],"consensus_categories":[],"category_scores_codex":[0.01447804,0.0003641687,0.0007152836,0.00291194,0.01870988,0.02677252,0.001789527,0.006399641,0.01174698],"category_scores_gemma":[0.02203184,0.0002443122,0.0004397501,0.003460076,0.04254468,0.02790839,0.01058455,0.01060527,0.004366545],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01102355,"about_ca_system_score_gemma":0.02023591,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01020805,"about_ca_topic_score_gemma":0.008069198,"domain_scores_codex":[0.9818122,0.009700108,0.0005128402,0.001591743,0.002562303,0.003820823],"domain_scores_gemma":[0.9824963,0.00284307,0.002073555,0.0009861749,0.002283358,0.009317677],"domain_codex":null,"domain_gemma":"incentives","domain_candidate":"incentives","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003057449,0.00006855108,0.003154532,0.00004958642,0.000008543448,0.0001386534,0.04643248,0.00005008035,0.00004501469,0.8695755,0.0526183,0.02782819],"study_design_scores_gemma":[0.00002536504,0.00004355631,0.002360578,0.0003358994,0.000008795006,0.0002994528,0.07721363,0.0001283985,0.00009036016,0.4818814,0.4375677,0.00004483227],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.01943733,0.01004725,0.0017472,0.7356663,0.005210678,0.00002659867,0.00006579041,0.00004813917,0.2277508],"genre_scores_gemma":[0.8669605,0.01035779,0.001860905,0.06768052,0.004780539,0.00009609324,0.0001225797,0.0001076466,0.04803346],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.985522,"threshold_uncertainty_score":0.07998186,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2126214972424438,"score_gpt":0.4886567326402965,"score_spread":0.2760352353978526,"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."}}