{"id":"W2055319746","doi":"10.1111/j.1745-3992.2004.tb00161.x","title":"Modeling Passing Rates on a Computer‐Based Medical Licensing Examination: An Application of Survival Data Analysis","year":2004,"lang":"en","type":"article","venue":"Educational Measurement Issues and Practice","topic":"Medical Education and Admissions","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Covariate; United States Medical Licensing Examination; Proportional hazards model; Survival analysis; Medical school; Variable (mathematics); Medicine; Medical education; Computer science; Psychology; Statistics; Surgery; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02718575,0.00102056,0.001371091,0.003094251,0.0007219603,0.001349464,0.002341066,0.001395439,0.004636914],"category_scores_gemma":[0.06481484,0.0005277035,0.003336468,0.002818816,0.00101438,0.001422114,0.001695725,0.002210493,0.0008208221],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001436393,"about_ca_system_score_gemma":0.002685471,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02209905,"about_ca_topic_score_gemma":0.0111866,"domain_scores_codex":[0.9889443,0.00837154,0.0004920274,0.0009090631,0.000742442,0.0005406158],"domain_scores_gemma":[0.9444001,0.04567847,0.004589197,0.002897535,0.001879389,0.000555339],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001578173,0.0007841812,0.6381362,0.0003170576,0.001648892,0.0004720283,0.001920214,0.2156324,0.0005281359,0.01888532,0.00279599,0.1173014],"study_design_scores_gemma":[0.0001622947,0.001240692,0.08098049,0.00009483654,0.0004667662,0.0003608507,0.0007111079,0.9003795,0.0007733025,0.01189611,0.00284679,0.0000873312],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.70603,0.0004793998,0.2850737,0.001922567,0.0001615148,0.001096981,0.002369596,0.0006874882,0.002178694],"genre_scores_gemma":[0.9437022,0.0003169373,0.04971965,0.0001391787,0.00007581282,0.001145715,0.00129503,0.00007283036,0.003532695],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02718575,"threshold_uncertainty_score":0.1437737,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2274161709273148,"score_gpt":0.4633927414507003,"score_spread":0.2359765705233855,"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."}}