{"id":"W4388632014","doi":"10.1177/15533506231211049","title":"Teaching Chest Tube Insertion by Blended Learning: A Multi-Dimensional Analysis","year":2023,"lang":"en","type":"article","venue":"Surgical Innovation","topic":"Surgical Simulation and Training","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University Health Centre; Royal College of Physicians and Surgeons of Canada; McGill University","funders":"McGill University","keywords":"Usability; Cognitive load; Blended learning; Reading (process); System usability scale; Medicine; Cognition; Learning effect; Educational technology; Multimedia; Computer science; Human–computer interaction; Psychology; Web usability; Mathematics education","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":[0.001741565,0.0005243711,0.0004992399,0.003696741,0.0003001776,0.001976346,0.000462715,0.0005139104,0.003060522],"category_scores_gemma":[0.003800244,0.0002002157,0.001142591,0.001707756,0.0003789905,0.0007990189,0.001224419,0.0002690735,0.0004544223],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007346828,"about_ca_system_score_gemma":0.0004280364,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000878301,"about_ca_topic_score_gemma":0.0005426399,"domain_scores_codex":[0.998767,0.0003880527,0.0001322819,0.0001790066,0.0004484195,0.0000852544],"domain_scores_gemma":[0.9982812,0.0008242623,0.0001654259,0.0001537393,0.0004802802,0.00009500424],"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":[0.001675521,0.00110683,0.1070974,0.0006225276,0.00034508,0.0002240933,0.00150693,0.03914556,0.02551744,0.001881451,0.00103604,0.8198411],"study_design_scores_gemma":[0.000111725,0.002721793,0.2534154,0.0002345085,0.000399577,0.001244434,0.002123681,0.7023826,0.02707479,0.00417308,0.005924194,0.0001942152],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7763121,0.001085949,0.216535,0.00019767,0.00005393205,0.0005935794,0.0004447125,0.0005496884,0.004227386],"genre_scores_gemma":[0.9434763,0.0003013916,0.05490378,0.00001684139,0.00001845376,0.000192104,0.0002012206,0.00003551815,0.0008544358],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003696741,"threshold_uncertainty_score":0.01023847,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05439083110747735,"score_gpt":0.3470460385422701,"score_spread":0.2926552074347927,"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."}}