{"id":"W4390107142","doi":"10.1101/2023.12.19.23300262","title":"Using Simulation-Based Experiential Learning to Increase Students’ Ability to Analyze Increasingly Complex Global Health Challenges: A Mixed Methods Study","year":2023,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Simulation-Based Education in Healthcare","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre for Global Health Research; University of Toronto; York University","funders":"York University","keywords":"Experiential learning; Interpersonal communication; Qualitative property; Psychology; Medical education; Social skills; Computer science; Knowledge management; Mathematics education; Medicine; Social psychology","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":[0.01936376,0.001071295,0.001135301,0.001712758,0.001904937,0.002283645,0.001717372,0.001448662,0.002624268],"category_scores_gemma":[0.01926846,0.0007555042,0.001224828,0.0009481031,0.001337009,0.00160131,0.002368997,0.001463988,0.0004676857],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001579968,"about_ca_system_score_gemma":0.003644345,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009051667,"about_ca_topic_score_gemma":0.001583471,"domain_scores_codex":[0.9924865,0.004694695,0.0005444673,0.000626783,0.0008014968,0.0008460804],"domain_scores_gemma":[0.9812074,0.0122788,0.001395054,0.001443712,0.002250463,0.001424511],"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":[0.007155919,0.1877377,0.1366431,0.002840247,0.0007002625,0.00164146,0.2474741,0.003238963,0.01385701,0.00250893,0.001786218,0.394416],"study_design_scores_gemma":[0.00596624,0.3082913,0.2830499,0.002731073,0.001040901,0.001600971,0.3095157,0.01548001,0.03122725,0.005137007,0.03530961,0.0006499487],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9962811,0.0001021708,0.001473931,0.0000981725,0.00001453006,0.001380937,0.00004981397,0.00001217237,0.0005871771],"genre_scores_gemma":[0.9830137,0.0003512091,0.008408465,0.0002618122,0.00004104823,0.006820305,0.00008638672,0.00001387948,0.00100323],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01936376,"threshold_uncertainty_score":0.1024066,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2427562625957739,"score_gpt":0.5497664392897166,"score_spread":0.3070101766939427,"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."}}