{"id":"W3216038349","doi":"10.2196/24372","title":"Learning Analytics Applied to Clinical Diagnostic Reasoning Using a Natural Language Processing–Based Virtual Patient Simulator: Case Study","year":2021,"lang":"en","type":"article","venue":"JMIR Medical Education","topic":"Simulation-Based Education in Healthcare","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Humanitas Research Hospital; Humanitas University","keywords":"Computer science; Test (biology); Representation (politics); Class (philosophy); Artificial intelligence; Analytics; Identification (biology); Virtual patient; Machine learning; Natural language processing; Data mining; Medical education; Medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002517267,0.0007070097,0.0004159624,0.001419739,0.000561296,0.001497199,0.001244247,0.001878762,0.001026077],"category_scores_gemma":[0.0119396,0.0003195787,0.0006711807,0.0007621878,0.001237648,0.0007416034,0.001309313,0.0009285892,0.0003364637],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009748738,"about_ca_system_score_gemma":0.001025432,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001373364,"about_ca_topic_score_gemma":0.001800017,"domain_scores_codex":[0.9972372,0.001465853,0.000243312,0.000271748,0.0005780839,0.0002037493],"domain_scores_gemma":[0.9887021,0.008427389,0.0006597773,0.0006743277,0.0006486443,0.0008878558],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001843043,0.01483176,0.3291468,0.001761436,0.0003553393,0.08223838,0.02331941,0.1851005,0.02788947,0.007776025,0.005272427,0.3204654],"study_design_scores_gemma":[0.0006549575,0.01326159,0.111093,0.0005102663,0.0002317658,0.07611699,0.01473245,0.678705,0.07266079,0.0100848,0.02155116,0.0003973602],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9783418,0.0001269657,0.01947232,0.0003353437,0.00001420068,0.0003769716,0.0001094955,0.0001009109,0.001121959],"genre_scores_gemma":[0.9755769,0.0001689977,0.02343359,0.00009325723,0.00001954245,0.0001452942,0.0001081298,0.0000181194,0.000436221],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002517267,"threshold_uncertainty_score":0.01331276,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03234728596496132,"score_gpt":0.4593433956697738,"score_spread":0.4269961097048125,"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."}}