{"id":"W4316143676","doi":"","title":"Opening Editorial: Selection and Recruitment in Medical Education","year":2018,"lang":"en","type":"article","venue":"DOAJ (DOAJ: Directory of Open Access Journals)","topic":"Medical Education and Admissions","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Selection (genetic algorithm); Medical education; Medicine; Computer science; Artificial intelligence","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.02633712,0.002658618,0.003988789,0.004380256,0.008220728,0.01826825,0.00565126,0.02169969,0.02896013],"category_scores_gemma":[0.1188017,0.00134145,0.004366387,0.001905103,0.008253604,0.008175953,0.004761575,0.0257397,0.01466672],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007286118,"about_ca_system_score_gemma":0.0121919,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001757112,"about_ca_topic_score_gemma":0.003494069,"domain_scores_codex":[0.966131,0.008345185,0.004252809,0.003758371,0.01518243,0.002330213],"domain_scores_gemma":[0.8841552,0.05986493,0.006476481,0.003767369,0.032201,0.01353501],"domain_codex":null,"domain_gemma":"incentives","domain_candidate":"incentives","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002054249,0.00001277227,0.00003254509,0.0002236353,0.000008770918,0.000060676,0.00008050155,0.00001609702,0.00002908081,0.0005559947,0.9948964,0.004063122],"study_design_scores_gemma":[0.00003840971,0.00005295573,0.0003095925,0.001232881,0.00002694542,0.0001700465,0.0002445467,0.00008343215,0.00009131858,0.001905914,0.9958153,0.00002862149],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.00003565544,0.001346193,0.0001112927,0.04610237,0.9514561,0.00002757037,0.00002852425,0.00003851907,0.0008536408],"genre_scores_gemma":[0.0004682416,0.00169218,0.0001626698,0.0246006,0.9684286,0.00004964523,0.00002645411,0.00006011177,0.00451152],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.9736629,"threshold_uncertainty_score":0.1392856,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3568683189569271,"score_gpt":0.6469917744556348,"score_spread":0.2901234554987077,"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."}}