{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.002446243,0.0001402987,0.0002800196,0.0002205732,0.0001076975,0.000004125166,0.0003150508,0.0003099648,0.000512138],"category_scores_gemma":[0.01275862,0.000106803,0.000009427109,0.0002127024,0.000279379,0.000168005,0.0001422783,0.0007829011,0.0001099452],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003958837,"about_ca_system_score_gemma":0.000659546,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000786588,"about_ca_topic_score_gemma":0.00005015593,"domain_scores_codex":[0.9984249,0.0001008172,0.0003497596,0.0004918111,0.0003612743,0.0002713627],"domain_scores_gemma":[0.9981019,0.000234913,0.0001126336,0.0005908734,0.0001423967,0.0008172426],"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":[0.0001917073,0.00005182829,0.02657238,0.0001769084,0.00008548207,0.000009481471,0.009159791,2.813296e-8,0.00223006,0.003682496,0.07011997,0.8877199],"study_design_scores_gemma":[0.001292885,0.0009164162,0.1097648,0.00150701,0.0003072865,0.001174895,0.007679624,0.000219796,0.000169798,0.001608742,0.8751308,0.0002279618],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6412187,0.01501065,0.0001616501,0.3360611,0.001755351,0.0002521939,0.000001091333,0.00005265541,0.00548655],"genre_scores_gemma":[0.9354513,0.01937792,0.0006918292,0.03118471,0.01169044,0.00002395942,0.0000953929,0.00002568418,0.001458796],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8874919,"threshold_uncertainty_score":0.9955573,"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."}}