{"id":"W3127336646","doi":"10.1111/ger.12536","title":"Harnessing group peer review for graduate training: What can peer review teach us?","year":2021,"lang":"en","type":"article","venue":"Gerodontology","topic":"Innovations in Medical Education","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Medicine; Medical education; Peer review; Training (meteorology)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.230256,0.001032933,0.0030387,0.003002674,0.005286369,0.01862474,0.004993056,0.01065964,0.01368957],"category_scores_gemma":[0.5278797,0.0007656764,0.001688023,0.002280657,0.009468596,0.02006937,0.008868769,0.009879977,0.006393895],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003279858,"about_ca_system_score_gemma":0.02243267,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001826281,"about_ca_topic_score_gemma":0.0038774,"domain_scores_codex":[0.8037483,0.1434276,0.005878945,0.006029494,0.03678155,0.00413413],"domain_scores_gemma":[0.3456057,0.4740628,0.02639434,0.03866952,0.0872037,0.02806397],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.0003239208,0.0005293388,0.006345297,0.004426535,0.0005675579,0.0002904623,0.006860673,0.0003792824,0.0006876388,0.0197358,0.1685253,0.7913283],"study_design_scores_gemma":[0.0007613755,0.002302964,0.02258245,0.02243469,0.00109588,0.001850751,0.01629131,0.00546335,0.003614239,0.2429171,0.6798958,0.000790154],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.0141828,0.07708523,0.04393936,0.7812216,0.03997729,0.0009302679,0.0001437305,0.001126526,0.0413933],"genre_scores_gemma":[0.493815,0.1205731,0.1097949,0.1618089,0.08911868,0.003201379,0.000305279,0.001172791,0.02020987],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.769744,"threshold_uncertainty_score":0.9492314,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1705299836443805,"score_gpt":0.4199171219588909,"score_spread":0.2493871383145104,"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."}}