{"id":"W2802899068","doi":"10.1017/cem.2018.174","title":"MP20: ImageSim - performance-based medical image interpretation learning system","year":2018,"lang":"en","type":"article","venue":"Canadian Journal of Emergency Medicine","topic":"Simulation-Based Education in Healthcare","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Hospital for Sick Children; University of Toronto","funders":"","keywords":"Commit; Medicine; Interpretation (philosophy); Emergency department; Presentation (obstetrics); Medical education; Radiology; Nursing; Computer 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":[0.0007269564,0.001267015,0.0006567952,0.0009935494,0.0002102502,0.0007651002,0.002258048,0.0009768277,0.03256427],"category_scores_gemma":[0.003142349,0.0004498022,0.0006189346,0.0004285501,0.0001737995,0.0009276819,0.001678354,0.0009575374,0.01132667],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005063868,"about_ca_system_score_gemma":0.0008590656,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001865644,"about_ca_topic_score_gemma":0.001314211,"domain_scores_codex":[0.9996939,0.00003749953,0.00003349992,0.00007109064,0.0001175626,0.00004652769],"domain_scores_gemma":[0.9993038,0.0001904319,0.00004514716,0.00008347917,0.0002483366,0.0001287307],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.005603421,0.001350856,0.006273512,0.001095536,0.0003865634,0.0006411884,0.0002635633,0.02167702,0.0781288,0.003148782,0.2245588,0.6568719],"study_design_scores_gemma":[0.001223626,0.001523353,0.01006664,0.0001791947,0.0002667736,0.001230862,0.00008934551,0.6446694,0.2188192,0.00527126,0.1163729,0.0002875241],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07009652,0.0008817693,0.4549836,0.0006633537,0.0003783083,0.002044385,0.01923356,0.4302227,0.02149582],"genre_scores_gemma":[0.4305601,0.001029376,0.4452546,0.001899927,0.0002607206,0.003079304,0.06025836,0.02451818,0.03313944],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03256427,"threshold_uncertainty_score":0.1089383,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06432030074203053,"score_gpt":0.3871702755298048,"score_spread":0.3228499747877743,"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."}}