{"id":"W4298362500","doi":"","title":"Comparing the traditional and Multiple Mini Interviews in the selection of post-graduate medical trainees","year":2015,"lang":"en","type":"article","venue":"DOAJ (DOAJ: Directory of Open Access Journals)","topic":"Medical Education and Admissions","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; University of Toronto","funders":"","keywords":"Selection (genetic algorithm); Medical education; Psychology; Graduate students; Mathematics education; Computer science; Medicine; Machine learning","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002984751,0.0001309771,0.0004487889,0.0002715144,0.00009477148,0.0001144983,0.0007656954,0.00006690246,0.005959553],"category_scores_gemma":[0.006481308,0.00007001793,0.00008947701,0.0005210249,0.0002221627,0.000312511,0.0001028152,0.0005427003,0.000002475745],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003550313,"about_ca_system_score_gemma":0.0006250493,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004785903,"about_ca_topic_score_gemma":0.0001483157,"domain_scores_codex":[0.9976394,0.0004042058,0.0006755771,0.0001662962,0.0009542949,0.0001602746],"domain_scores_gemma":[0.9979059,0.0007917666,0.0003058966,0.0001738568,0.0002340592,0.0005885919],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005954379,0.002300658,0.689616,0.0002464576,0.0002050285,0.00003268752,0.01192926,0.00002433607,0.01387201,0.0003742841,0.2490411,0.03176273],"study_design_scores_gemma":[0.001498868,0.00004309413,0.9799575,0.0008176721,0.00006497431,0.0001772141,0.003367001,0.001825848,0.001255975,0.000987311,0.009898098,0.0001064398],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9787157,0.002895212,0.00007494845,0.01551471,0.0002717538,0.000391897,0.000007803629,0.000007839599,0.002120151],"genre_scores_gemma":[0.9955291,0.00116726,0.00009612538,0.002876789,0.0001941927,0.00002043128,0.00001878178,0.00001081641,0.00008647353],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2903415,"threshold_uncertainty_score":0.9949492,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6555930555645458,"score_gpt":0.5939813482727078,"score_spread":0.06161170729183807,"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."}}