{"id":"W4377378862","doi":"10.5334/pme.898","title":"What can Designing Learning-by-Concordance Clinical Reasoning Cases Teach Us about Instruction in the Health Sciences?","year":2023,"lang":"en","type":"article","venue":"Perspectives on Medical Education","topic":"Clinical Reasoning and Diagnostic Skills","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Experiential learning; Thematic analysis; Cognitive apprenticeship; Psychology; Dialogic; Medical education; Computer science; Mathematics education; Pedagogy; Qualitative research; Medicine","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":[0.05926636,0.0008719994,0.0006908719,0.001596143,0.002509559,0.007964552,0.004130315,0.003936185,0.004527909],"category_scores_gemma":[0.1842377,0.0007709251,0.0008864466,0.001062101,0.007297391,0.008648085,0.004629325,0.002758444,0.001557336],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004203745,"about_ca_system_score_gemma":0.007631188,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008734072,"about_ca_topic_score_gemma":0.00174978,"domain_scores_codex":[0.9364955,0.05088231,0.002836592,0.00237097,0.00577023,0.001644285],"domain_scores_gemma":[0.8298108,0.1361243,0.00987522,0.01274491,0.007782581,0.00366222],"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":[0.0003217882,0.001685717,0.0238474,0.006171946,0.00007156569,0.001562576,0.2498611,0.002534877,0.005327763,0.04743668,0.01370275,0.6474758],"study_design_scores_gemma":[0.0004731826,0.003632111,0.0260547,0.01611944,0.0002696864,0.007868691,0.2226324,0.01884936,0.03868283,0.2187175,0.4462021,0.0004979664],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3760148,0.004109215,0.4721625,0.06044104,0.001034112,0.006191478,0.0003501099,0.001752222,0.0779444],"genre_scores_gemma":[0.5537879,0.001488683,0.4376095,0.002578797,0.000166362,0.001803863,0.0001898546,0.0001673065,0.002207824],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.05926636,"threshold_uncertainty_score":0.3134342,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04419947260508802,"score_gpt":0.4467894309338235,"score_spread":0.4025899583287355,"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."}}