{"id":"W2492228671","doi":"10.1007/s40670-016-0306-z","title":"Assessment Driven Learning: the Use of Higher-Order and Discipline-Integrated Questions on Gross Anatomy Practical Examinations","year":2016,"lang":"en","type":"article","venue":"Medical Science Educator","topic":"Innovations in Medical Education","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"University of Calgary","keywords":"Gross anatomy; Modalities; Identification (biology); Pairwise comparison; Point (geometry); Medical education; Mathematics education; Psychology; Medicine; Computer science; Anatomy; Artificial intelligence; Mathematics; Biology; Social science; Ecology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001590899,0.0001259779,0.0001861619,0.0002320587,0.00043361,0.00005155117,0.0002186848,0.000109643,0.001087506],"category_scores_gemma":[0.02491219,0.00006002409,0.00002849513,0.00178019,0.003378731,0.0002961128,0.00009631318,0.0005606197,0.00002239693],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002873779,"about_ca_system_score_gemma":0.003593001,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005478199,"about_ca_topic_score_gemma":0.00000842784,"domain_scores_codex":[0.9972215,0.0001352725,0.0003773566,0.0003693169,0.001579205,0.0003173052],"domain_scores_gemma":[0.9974113,0.001018679,0.0001443256,0.0003724453,0.0007058537,0.0003473987],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00006081692,0.00477048,0.2688621,0.00008346648,0.00008817483,0.00002721845,0.001962313,0.000006641433,0.008920757,0.3628386,0.06803738,0.284342],"study_design_scores_gemma":[0.0006990953,0.0004092683,0.7920558,0.0004692358,0.00006120934,0.00006601614,0.001184678,0.002318568,0.0003767445,0.0003196205,0.201886,0.0001538094],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7866543,0.000009239026,0.004389833,0.2069893,0.001032817,0.0003082403,0.000003184556,0.00004202569,0.0005710549],"genre_scores_gemma":[0.9861407,0.00003197286,0.0100454,0.00145432,0.00028543,0.00008187791,0.000009497936,0.00001093221,0.001939817],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5231937,"threshold_uncertainty_score":0.9998257,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04911595686991343,"score_gpt":0.4458030795416657,"score_spread":0.3966871226717523,"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."}}