{"id":"W2182003369","doi":"10.1002/j.0022-0337.2014.78.4.tb05711.x","title":"Developing a Customized Multiple Interview for Dental School Admissions","year":2014,"lang":"en","type":"article","venue":"Journal of Dental Education","topic":"Medical Education and Admissions","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Telephone interview; Medical education; Interview; Psychology; Semi-structured interview; Process (computing); Reliability (semiconductor); MEDLINE; Personnel selection; Applied psychology; Medicine; Computer science; Qualitative research","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.08173875,0.001266368,0.0008133925,0.00444067,0.003034691,0.00335196,0.004219703,0.001626224,0.01108464],"category_scores_gemma":[0.1071859,0.001400411,0.00170277,0.002642421,0.002000257,0.003845739,0.01079302,0.003231567,0.004641954],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004837642,"about_ca_system_score_gemma":0.01146603,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002129944,"about_ca_topic_score_gemma":0.005816727,"domain_scores_codex":[0.9215927,0.05815434,0.006731368,0.003536127,0.007506076,0.002479309],"domain_scores_gemma":[0.9292424,0.04305736,0.005250239,0.007809439,0.01170006,0.002940399],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006700745,0.001318769,0.009659206,0.001989131,0.00005425257,0.001405532,0.05591235,0.006023314,0.02251685,0.010703,0.0126379,0.8771095],"study_design_scores_gemma":[0.001466056,0.0112597,0.05433384,0.007623251,0.0002701388,0.00588666,0.1890772,0.05767632,0.0674295,0.05375541,0.5497411,0.00148082],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.09358554,0.0002680515,0.7871635,0.00226281,0.0006828725,0.09087332,0.001041767,0.004527383,0.01959472],"genre_scores_gemma":[0.03932686,0.0001583767,0.9296727,0.0003186259,0.00006695222,0.02680119,0.0003942893,0.0001794221,0.003081594],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.08173875,"threshold_uncertainty_score":0.432281,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0476925658338119,"score_gpt":0.3964205355077162,"score_spread":0.3487279696739043,"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."}}