{"id":"W2894478196","doi":"10.1097/acm.0000000000002465","title":"Data, Big and Small: Emerging Challenges to Medical Education Scholarship","year":2018,"lang":"en","type":"article","venue":"Academic Medicine","topic":"Radiology practices and education","field":"Medicine","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"South Health Campus; University of Calgary","funders":"","keywords":"Scholarship; CLARITY; Public relations; Medical education; Big data; Data collection; Stewardship (theology); Political science; Sociology; Engineering ethics; Medicine; Computer science; Social science; Engineering; Politics","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":[0.2275933,0.0007661559,0.002216778,0.008771178,0.01245373,0.0428024,0.01027894,0.01354833,0.009964566],"category_scores_gemma":[0.3595543,0.001287144,0.001624815,0.01389603,0.04963678,0.05379818,0.03134375,0.02755737,0.003020343],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01256801,"about_ca_system_score_gemma":0.05345646,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005102865,"about_ca_topic_score_gemma":0.007324079,"domain_scores_codex":[0.8637664,0.07585827,0.01099232,0.009679233,0.03443173,0.005272122],"domain_scores_gemma":[0.3053375,0.5513297,0.01384049,0.03750174,0.05517044,0.03682008],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001510914,0.0002135213,0.01006636,0.003675088,0.0001273386,0.0006553225,0.02661108,0.001080764,0.0003708668,0.442481,0.1958996,0.3186679],"study_design_scores_gemma":[0.00004408682,0.0001004594,0.003010729,0.004387948,0.00002459278,0.0004529204,0.03764793,0.001670205,0.0003334581,0.5512751,0.4009159,0.0001367137],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.002313139,0.0169545,0.007818663,0.9652768,0.003770941,0.00003148803,0.0001437282,0.000112104,0.003578725],"genre_scores_gemma":[0.3470412,0.1059819,0.1077189,0.3626528,0.06165594,0.0007418046,0.001319403,0.001056962,0.01183102],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.7724067,"threshold_uncertainty_score":0.9525149,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.236706911822794,"score_gpt":0.4588209298710123,"score_spread":0.2221140180482183,"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."}}