{"id":"W2531188243","doi":"10.1097/acm.0000000000001448","title":"Avoiding Common Data Analysis Pitfalls in Health Professions Education Research","year":2016,"lang":"en","type":"article","venue":"Academic Medicine","topic":"Healthcare Systems and Reforms","field":"Economics, Econometrics and Finance","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Health professions; Medical education; Academic medicine; Medicine; Family medicine; Political science; Health care","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":[],"consensus_categories":[],"category_scores_codex":[0.01825132,0.00009993248,0.0005950036,0.001265865,0.0002328046,0.000004488609,0.0006289052,0.0002128307,0.0003173529],"category_scores_gemma":[0.002299487,0.00005948134,0.00002522134,0.001605214,0.0001049887,0.0002412703,0.0001820999,0.001062415,0.0001964551],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000411166,"about_ca_system_score_gemma":0.0003077283,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02122633,"about_ca_topic_score_gemma":0.0006554119,"domain_scores_codex":[0.9971902,0.0003266526,0.00133626,0.0005291319,0.0001233842,0.0004944118],"domain_scores_gemma":[0.9981682,0.0002628369,0.0003978279,0.0008232814,0.00004450075,0.0003033204],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001505672,0.00005258253,0.6865771,0.0003502596,0.0001149155,0.000002710993,0.01097083,0.00000200794,0.0001016416,0.1652073,0.03294407,0.1036615],"study_design_scores_gemma":[0.001726018,0.0002651612,0.4865454,0.005041846,0.00001352399,0.00001419351,0.01590523,0.0009244707,0.00001565496,0.09678973,0.3922769,0.0004818252],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5581847,0.04167455,0.006470546,0.375415,0.00234568,0.001578298,0.0002027376,0.0000758417,0.01405261],"genre_scores_gemma":[0.9845223,0.008010435,0.00003654725,0.001000908,0.0005286579,0.00003550703,0.00008155309,0.00001399833,0.005770048],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4263376,"threshold_uncertainty_score":0.9852914,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3527637169504381,"score_gpt":0.4862199925217255,"score_spread":0.1334562755712875,"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."}}