{"id":"W2076628217","doi":"10.3109/0142159x.2014.970986","title":"Learning medical professionalism with the online concordance-of-judgment learning tool (CJLT): A pilot study","year":2014,"lang":"en","type":"article","venue":"Medical Teacher","topic":"Innovations in Medical Education","field":"Medicine","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal; Université de Montréal","funders":"","keywords":"Concordance; Medical education; Psychology; Online learning; MEDLINE; Medicine; Computer science; Multimedia; Political science","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":[0.01169453,0.0007211369,0.0005806629,0.0009478055,0.001142214,0.0009540356,0.0009977159,0.0008239606,0.002611953],"category_scores_gemma":[0.02160244,0.0006003621,0.0005451693,0.0006109655,0.001046304,0.001428454,0.001856434,0.00129865,0.0007132153],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001044921,"about_ca_system_score_gemma":0.001714682,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001320606,"about_ca_topic_score_gemma":0.002933423,"domain_scores_codex":[0.9941441,0.003686964,0.0003031801,0.0003982646,0.0007262209,0.0007412619],"domain_scores_gemma":[0.9788013,0.01325596,0.001262848,0.001349886,0.002435305,0.002894791],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.006674341,0.1938923,0.2540385,0.001598209,0.0001553893,0.005171841,0.1285998,0.002693517,0.01765046,0.0006016312,0.003327427,0.3855965],"study_design_scores_gemma":[0.004770633,0.2755343,0.5623631,0.0003754255,0.0002675331,0.00660615,0.07253791,0.01451276,0.0456605,0.001078313,0.01593935,0.0003539796],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.997584,0.00002220866,0.001100225,0.00003668911,0.000005432701,0.0007454551,0.00002277488,0.00001974454,0.0004634376],"genre_scores_gemma":[0.990688,0.00008723142,0.007336249,0.0001002135,0.00001805922,0.0009982607,0.00008502011,0.00001543423,0.0006715063],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01169453,"threshold_uncertainty_score":0.06184727,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0400423158821744,"score_gpt":0.3681613373369285,"score_spread":0.3281190214547541,"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."}}