{"id":"W2132790208","doi":"10.3109/0142159x.2013.801937","title":"In-group bias in residency selection","year":2013,"lang":"en","type":"article","venue":"Medical Teacher","topic":"Diversity and Career in Medicine","field":"Social Sciences","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Matching (statistics); Medical school; Selection (genetic algorithm); Observational study; United States Medical Licensing Examination; Propensity score matching; Medicine; Psychology; Medical education; Selection bias; Family medicine; Internal medicine; Computer science","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":[0.002485658,0.00004475465,0.00009494312,0.00008786473,0.00006527382,0.00002323416,0.0002450453,0.0001651877,0.0295313],"category_scores_gemma":[0.001753683,0.00003958784,0.00001981555,0.0003849867,0.0001946693,0.0002034012,0.00003628806,0.0003534639,0.0004145541],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000118066,"about_ca_system_score_gemma":0.0001284787,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.03529783,"about_ca_topic_score_gemma":0.02396196,"domain_scores_codex":[0.9982827,0.000294637,0.0001258416,0.0001258832,0.0009350323,0.0002359074],"domain_scores_gemma":[0.999696,0.00005488546,0.00001787952,0.00005198893,0.00002204014,0.0001572524],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000004997425,0.0001540463,0.8328475,0.00000677678,0.000003536232,0.00004219884,0.01622705,3.301931e-7,0.000007801529,0.006826417,0.1233838,0.02049555],"study_design_scores_gemma":[0.002159614,0.0001527132,0.4824592,0.0002702554,0.00001263328,0.000003532981,0.06478905,0.0006677046,0.000009275369,0.03093354,0.4181671,0.0003753559],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.82511,0.00009337314,0.00002630697,0.02422696,0.00032158,0.0001356462,4.93392e-8,0.00003249847,0.1500535],"genre_scores_gemma":[0.9835238,0.00007964976,0.0000363754,0.001291574,0.0003877534,0.00001233073,9.0238e-7,0.000003086691,0.01466448],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3503883,"threshold_uncertainty_score":0.9938482,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05166279835909271,"score_gpt":0.3284511216368026,"score_spread":0.2767883232777099,"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."}}