{"id":"W2008344668","doi":"10.1111/medu.12564","title":"Feedback fairs: low‐tech, high‐impact knowledge to action","year":2014,"lang":"en","type":"article","venue":"Medical Education","topic":"Innovations in Medical Education","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research","keywords":"Library science; Computer science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.06226454,0.001018452,0.0007863767,0.003492313,0.005771832,0.007884253,0.002518933,0.005538833,0.05088058],"category_scores_gemma":[0.1718074,0.0005533815,0.001151463,0.001132886,0.008257958,0.01112812,0.0104657,0.003726663,0.003768737],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004215564,"about_ca_system_score_gemma":0.009323824,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002060514,"about_ca_topic_score_gemma":0.003172531,"domain_scores_codex":[0.9612848,0.02553043,0.0009548272,0.001765447,0.007489784,0.002974868],"domain_scores_gemma":[0.8163954,0.1296988,0.01098668,0.01548411,0.009445573,0.01798948],"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":[0.001777567,0.003255555,0.01280261,0.001479621,0.0001528877,0.0003126014,0.0113891,0.00246949,0.00201004,0.2462021,0.1402821,0.5778664],"study_design_scores_gemma":[0.001764334,0.002663826,0.0252855,0.002852648,0.0002850954,0.0003964932,0.00999939,0.009547888,0.00387549,0.727981,0.2149548,0.0003934707],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1679677,0.004826529,0.2443185,0.1520783,0.01497967,0.0041283,0.001350502,0.01131743,0.399033],"genre_scores_gemma":[0.9218243,0.000714844,0.03673206,0.008200731,0.001401134,0.001427604,0.0002240213,0.0002962769,0.02917896],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.06226454,"threshold_uncertainty_score":0.3292903,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01289927928066877,"score_gpt":0.3900848669369758,"score_spread":0.3771855876563071,"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."}}