{"id":"W4400890026","doi":"10.1002/ase.2485","title":"Artificial intelligence and anatomy grading: Opportunities for more meaningful learning","year":2024,"lang":"en","type":"letter","venue":"Anatomical Sciences Education","topic":"Anatomy and Medical Technology","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"","keywords":"Grading (engineering); Psychology; Medical education; Cognitive science; Artificial intelligence; Computer science; Medicine; Biology","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":[],"consensus_categories":[],"category_scores_codex":[0.006343311,0.0004242272,0.0006766766,0.0007578333,0.004978971,0.00781631,0.001385314,0.06874314,0.01878582],"category_scores_gemma":[0.02497709,0.0005104207,0.0007604242,0.0004668478,0.004574023,0.005451185,0.003360704,0.03553549,0.008383359],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004353349,"about_ca_system_score_gemma":0.007335358,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008080156,"about_ca_topic_score_gemma":0.02934463,"domain_scores_codex":[0.9943134,0.001676534,0.0004859636,0.0004904512,0.002288194,0.0007454167],"domain_scores_gemma":[0.9843871,0.008719277,0.0005079147,0.0004368447,0.00282847,0.00312046],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003351812,0.00005831577,0.0007521865,0.00003156577,0.000005816711,0.001102112,0.0002196388,0.0000824668,0.0002289065,0.0172347,0.9618251,0.0184257],"study_design_scores_gemma":[0.00006033541,0.00005296554,0.001447926,0.0001655761,0.000008112542,0.001776834,0.0006919735,0.0009816336,0.0001628124,0.04574239,0.9488637,0.00004558936],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.0003885036,0.0003306695,0.0003162151,0.9826148,0.005494002,0.000007683445,0.00001268131,0.00001685177,0.01081857],"genre_scores_gemma":[0.01072716,0.0008059188,0.001149874,0.900547,0.03200636,0.00003804314,0.00001918992,0.00003192738,0.05467448],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.06874314,"threshold_uncertainty_score":0.06284475,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06596986211846821,"score_gpt":0.319267603751526,"score_spread":0.2532977416330578,"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."}}