{"id":"W2146039396","doi":"10.1017/cem.2014.58","title":"What adult electrocardiogram (ECG) diagnoses and/or findings do residents in emergency medicine need to know?","year":2015,"lang":"en","type":"article","venue":"Canadian Journal of Emergency Medicine","topic":"ECG Monitoring and Analysis","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"Jewish General Hospital; McGill University; McGill University Health Centre","funders":"University of Alberta; McMaster University; McGill University; Dalhousie University; Université Laval","keywords":"Medical diagnosis; Medicine; Delphi method; Context (archaeology); Likert scale; Categorization; Delphi; Medical emergency; Psychology; Pathology; Artificial intelligence; Computer science","routes":{"ca_aff":true,"ca_fund":true,"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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001579064,0.0003664028,0.001157414,0.002163888,0.0001142933,0.00001307113,0.0003207836,0.0001634763,0.002006494],"category_scores_gemma":[0.00724107,0.0002568474,0.0001779417,0.002347672,0.000128099,0.0003667889,0.00002451185,0.0005950485,0.00002004019],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003271237,"about_ca_system_score_gemma":0.0008438778,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02551051,"about_ca_topic_score_gemma":0.041306,"domain_scores_codex":[0.9961686,0.0001313324,0.001739444,0.0003700883,0.0008353652,0.0007552225],"domain_scores_gemma":[0.9943696,0.00009010023,0.0003438048,0.0003774869,0.001292024,0.003526945],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002763201,0.0000452372,0.6206576,0.0001033105,0.0002676598,0.0007611511,0.005940335,0.00001518161,0.0006086105,0.00002731159,0.3664515,0.004845789],"study_design_scores_gemma":[0.01961379,0.02446996,0.5312313,0.02531843,0.004325583,0.001016492,0.09708775,0.0002578236,0.0007161996,0.002624711,0.2913897,0.001948233],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8891994,0.04402621,0.00007949363,0.04849562,0.01605255,0.00036134,0.000003802484,0.00002026762,0.001761361],"genre_scores_gemma":[0.9360259,0.05177137,0.0001745573,0.0004480809,0.005160239,0.00001612292,0.00001287872,0.00006347287,0.006327356],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09114742,"threshold_uncertainty_score":0.9999884,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05867122813229186,"score_gpt":0.3579352035661658,"score_spread":0.299263975433874,"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."}}