{"id":"W2922331177","doi":"10.4253/wjge.v11.i3.209","title":"Simulation in endoscopy: Practical educational strategies to improve learning","year":2019,"lang":"en","type":"review","venue":"World Journal of Gastrointestinal Endoscopy","topic":"Simulation-Based Education in Healthcare","field":"Medicine","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hospital for Sick Children; University of Toronto; St. Michael's Hospital; SickKids Foundation; Western University","funders":"","keywords":"Debriefing; Pace; Computer science; Simulation training; Learning curve; Medical education; Focus (optics); Grounded theory; Training (meteorology); Medicine; Simulation; Qualitative research","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.001292996,0.0005874058,0.002150301,0.002281367,0.00008800988,0.0001296931,0.0002577554,0.000137327,0.0007084025],"category_scores_gemma":[0.005455201,0.0005248325,0.0005295463,0.001335692,0.00007419741,0.0004247097,0.00005653526,0.002692587,0.0002485847],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001584029,"about_ca_system_score_gemma":0.01255727,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005744699,"about_ca_topic_score_gemma":0.00001648949,"domain_scores_codex":[0.9948376,0.0006524341,0.002465444,0.0005216618,0.0009126841,0.0006101952],"domain_scores_gemma":[0.9854596,0.009988682,0.002185186,0.0004147499,0.001363701,0.0005881435],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.008343284,0.004492878,0.1711923,0.1204628,0.001033875,0.001392392,0.003121491,0.3450167,0.0003522197,0.005267691,0.005466864,0.3338574],"study_design_scores_gemma":[0.007125094,0.009701869,0.007903591,0.3225904,0.003959139,0.01474862,0.003773871,0.00515857,0.0000114559,0.0006633064,0.6224375,0.001926628],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"methods","genre_scores_codex":[0.0008626471,0.9768081,0.007125528,0.00575559,0.003426918,0.003855661,0.00003132514,0.00007307199,0.002061143],"genre_scores_gemma":[0.07282439,0.4377768,0.467349,0.001103579,0.01162119,0.0003494497,0.0005344001,0.0007338487,0.00770734],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.6169706,"threshold_uncertainty_score":0.9997203,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08525308631649026,"score_gpt":0.4610367554328888,"score_spread":0.3757836691163985,"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."}}