{"id":"W4379600149","doi":"10.1097/acm.0000000000005290","title":"Deep Learning Model for Automated Trainee Assessment During High-Fidelity Simulation","year":2023,"lang":"en","type":"article","venue":"Academic Medicine","topic":"Simulation-Based Education in Healthcare","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; SickKids Foundation; Hospital for Sick Children","funders":"Medical Council of Canada","keywords":"Computer science; Inter-rater reliability; Deep learning; Modalities; Competence (human resources); Artificial intelligence; Medical physics; Simulation; Machine learning; Medicine","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002407505,0.0008091111,0.0006593111,0.0007999075,0.0003809382,0.000919973,0.001402389,0.001095505,0.002205474],"category_scores_gemma":[0.006416257,0.0004140117,0.000830117,0.0003605636,0.000441388,0.0008188764,0.0008941495,0.001498693,0.0004831135],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00224332,"about_ca_system_score_gemma":0.002006561,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0259055,"about_ca_topic_score_gemma":0.01499671,"domain_scores_codex":[0.9993187,0.0002401366,0.00004209638,0.0001574414,0.0001303253,0.0001113684],"domain_scores_gemma":[0.9971766,0.00152911,0.0002668623,0.000100824,0.0008123863,0.0001141253],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001331155,0.00007169945,0.004139653,0.00004051158,0.00003761574,0.00004667575,0.00005499259,0.9602028,0.0005971181,0.001231079,0.000622614,0.03282218],"study_design_scores_gemma":[0.000003550502,0.00001895137,0.0002465977,0.000004604437,0.000004913974,0.000005712145,0.000003290819,0.9990242,0.0001782071,0.0004353764,0.00007193079,0.000002630519],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1529727,0.0005050686,0.8396245,0.0008923991,0.00006681505,0.0003053519,0.0004668205,0.001518477,0.003647808],"genre_scores_gemma":[0.9323643,0.0001795449,0.0631704,0.0001801792,0.00002211275,0.0004125373,0.0003968449,0.00004813067,0.003225913],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0259055,"threshold_uncertainty_score":0.05150938,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09712288966503065,"score_gpt":0.4675052864311365,"score_spread":0.3703823967661059,"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."}}