{"id":"W4396700068","doi":"10.2196/58355","title":"Assessing AI Awareness and Identifying Essential Competencies: Insights From Key Stakeholders in Integrating AI Into Medical Education","year":2024,"lang":"en","type":"article","venue":"JMIR Medical Education","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Bundesministerium für Bildung und Forschung; Eberhard Karls Universität Tübingen; Deutsche Forschungsgemeinschaft","keywords":"Preprint; Key (lock); Knowledge management; Psychology; Data science; Computer science; Engineering ethics; Artificial intelligence; Engineering; World Wide Web; Computer security","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006719792,0.000237278,0.0003521278,0.0005350896,0.0002417396,0.0003958453,0.0001756409,0.0004689652,0.0009161656],"category_scores_gemma":[0.003198495,0.0002108343,0.00006889592,0.0007861772,0.0002566456,0.0009731986,0.00005935848,0.001177393,0.00005133634],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005271232,"about_ca_system_score_gemma":0.02214885,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01516377,"about_ca_topic_score_gemma":0.004064638,"domain_scores_codex":[0.9967301,0.0002134514,0.0009370985,0.0006408449,0.001164154,0.0003143769],"domain_scores_gemma":[0.9980975,0.0004417261,0.0001108558,0.0002768761,0.0003395055,0.0007335339],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.00004298362,0.001167913,0.03309001,0.001270889,0.00003719383,0.00003271331,0.05420133,0.000001175627,0.001162963,0.005346794,0.006513522,0.8971325],"study_design_scores_gemma":[0.0008567012,0.0004610174,0.1239948,0.06451771,0.0004094101,0.0004819814,0.5025237,0.1443809,0.007914633,0.1015923,0.0509211,0.001945772],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9388589,0.004172841,0.004199186,0.045949,0.005813816,0.0005294806,8.659662e-7,0.0001252455,0.000350698],"genre_scores_gemma":[0.9883428,0.0003140988,0.0008650112,0.007441085,0.002268862,0.0002789938,0.0003648211,0.00003631335,0.00008807635],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8951867,"threshold_uncertainty_score":0.9999971,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1277909840246013,"score_gpt":0.4891230749638896,"score_spread":0.3613320909392883,"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."}}