{"id":"W2911594032","doi":"10.1109/weef-gedc.2018.8629758","title":"What Engineering Admissions Can Learn from Medical School Admissions","year":2018,"lang":"en","type":"article","venue":"2018 World Engineering Education Forum - Global Engineering Deans Council (WEEF-GEDC)","topic":"Medical Education and Admissions","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Cognition; Diversity (politics); Process (computing); Medical education; Cultural diversity; Medical school; Cognitive skill; Psychology; Medical ethics; Medicine; Computer science; Political science; Psychiatry","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":["metaresearch","metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007271284,0.0009416041,0.0008800879,0.0005041997,0.0003482189,0.0002905816,0.0007475299,0.0005504331,0.02252485],"category_scores_gemma":[0.03647177,0.0009252555,0.0003732103,0.001952528,0.00009653506,0.000583999,0.0002235271,0.001415269,0.0006621045],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003272811,"about_ca_system_score_gemma":0.02111361,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004959169,"about_ca_topic_score_gemma":0.0002414411,"domain_scores_codex":[0.9936594,0.00003491819,0.001162846,0.001083759,0.002563593,0.001495437],"domain_scores_gemma":[0.9817156,0.0003183479,0.0001870323,0.001420215,0.001006913,0.01535192],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002156155,0.00258492,0.003146631,0.001074252,0.001193399,0.0001317551,0.001746675,0.01257651,0.009979479,0.01424832,0.9394695,0.01363294],"study_design_scores_gemma":[0.001220742,0.0001621955,0.004494106,0.003782475,0.0002363965,0.0001774187,0.0005093129,0.06082936,0.0006380686,0.00008158581,0.9268255,0.001042853],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.2836899,0.03773154,0.05791447,0.362573,0.1855514,0.008978602,0.001224646,0.01893738,0.04339897],"genre_scores_gemma":[0.8919106,0.001105313,0.02767963,0.0175278,0.01074214,0.0005620028,0.001038271,0.0005921618,0.04884205],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6082207,"threshold_uncertainty_score":0.9993198,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02210087307199139,"score_gpt":0.2791190136054275,"score_spread":0.2570181405334361,"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."}}