{"id":"W2048465014","doi":"10.1111/medu.12547","title":"Seeking inclusion in an exclusive process: discourses of medical school student selection","year":2014,"lang":"en","type":"article","venue":"Medical Education","topic":"Medical Education and Admissions","field":"Medicine","cited_by":98,"is_retracted":false,"has_abstract":true,"ca_institutions":"The Wilson Centre; University of Toronto; McGill University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Inclusion (mineral); Selection (genetic algorithm); Medical school; Process (computing); Medical education; Psychology; Medicine; Social psychology; Computer science","routes":{"ca_aff":true,"ca_fund":true,"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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001535989,0.0001444172,0.0003280255,0.0002934877,0.0001476212,0.00001452516,0.000316328,0.0003105243,0.013873],"category_scores_gemma":[0.03017481,0.0001117914,0.00005044988,0.0005567071,0.0001469566,0.0001504927,0.0002212531,0.0006188981,0.00001705995],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001223908,"about_ca_system_score_gemma":0.01173257,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008962501,"about_ca_topic_score_gemma":0.000083766,"domain_scores_codex":[0.9959043,0.0002279414,0.0006088297,0.0003329633,0.002684055,0.0002419566],"domain_scores_gemma":[0.9967384,0.0001447532,0.0001681002,0.0002403135,0.0002054768,0.002502985],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0002874188,0.0245882,0.348802,0.001290979,0.00005662065,0.00001344435,0.02685333,0.00001753832,0.003537039,0.005259706,0.02414205,0.5651517],"study_design_scores_gemma":[0.0121676,0.003222778,0.7153811,0.0178042,0.0003696886,0.0004451598,0.04458456,0.1073227,0.004707229,0.008751229,0.08395179,0.001292039],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9000049,0.0001478673,0.001186707,0.09527037,0.0008201328,0.000400237,3.907652e-7,0.00005417857,0.002115242],"genre_scores_gemma":[0.9828461,0.00006124777,0.0002999472,0.01528482,0.0009247623,0.00007902981,0.00007494215,0.0000182593,0.0004109017],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5638596,"threshold_uncertainty_score":0.99387,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01281927524133561,"score_gpt":0.4317973367184577,"score_spread":0.418978061477122,"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."}}