{"id":"W2144038358","doi":"10.36834/cmej.36521","title":"Does Applying Biomedical Knowledge Improve Diagnostic Performance When Solving Electrolyte Problems?","year":2010,"lang":"en","type":"article","venue":"Canadian Medical Education Journal","topic":"Clinical Reasoning and Diagnostic Skills","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Odds ratio; Odds; Logistic regression; Medicine; Medical education; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008013666,0.0002775325,0.0003716544,0.0006794802,0.0003270089,0.001049779,0.0005785719,0.0005791362,0.004812202],"category_scores_gemma":[0.06360721,0.0001304081,0.0003648023,0.0005333175,0.001150921,0.0009307305,0.0008251078,0.0004240671,0.0004984437],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00162244,"about_ca_system_score_gemma":0.003835195,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01460383,"about_ca_topic_score_gemma":0.01768627,"domain_scores_codex":[0.9940949,0.003093351,0.0004033995,0.0004931288,0.001616117,0.0002990762],"domain_scores_gemma":[0.9621837,0.02479244,0.005801644,0.0009697194,0.00446029,0.001792269],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005553684,0.0004546944,0.7858766,0.001248737,0.0001623471,0.0002064168,0.001389023,0.0008336403,0.00240889,0.0005125746,0.002426873,0.2039248],"study_design_scores_gemma":[0.000107888,0.001240504,0.9840921,0.0007703797,0.0001755359,0.0007926181,0.001194799,0.001751309,0.003731692,0.001430971,0.004668801,0.00004326205],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9647642,0.009455102,0.004492552,0.01065575,0.0001419384,0.0001144731,0.0003878391,0.00007222579,0.009915934],"genre_scores_gemma":[0.9913731,0.002669859,0.004062631,0.0009415352,0.0001082632,0.00002752066,0.0001131644,0.000009418315,0.0006945479],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01460383,"threshold_uncertainty_score":0.04238081,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00792698013410816,"score_gpt":0.2946518359373324,"score_spread":0.2867248558032243,"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."}}