{"id":"W2760488410","doi":"10.1016/j.cjca.2017.07.163","title":"DEVELOPING A CASE DEFINITION FOR CONGESTIVE HEART FAILURE USING PRIMARY CARE EMR DATA","year":2017,"lang":"en","type":"article","venue":"Canadian Journal of Cardiology","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Medicine; Heart failure; Medical emergency; Medical record; Intensive care medicine; Health care; Identification (biology); Best practice; Family medicine; Emergency medicine; Cardiology; Internal medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004722942,0.0008949664,0.000576971,0.005727237,0.001365676,0.003922442,0.001962527,0.001746384,0.003590384],"category_scores_gemma":[0.02146501,0.0005333371,0.001561846,0.002224708,0.0008918912,0.003399485,0.003079773,0.001559574,0.0008653405],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001782531,"about_ca_system_score_gemma":0.002908969,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01218561,"about_ca_topic_score_gemma":0.0154594,"domain_scores_codex":[0.9945022,0.001357328,0.001399432,0.0008941223,0.001450917,0.000396146],"domain_scores_gemma":[0.9865219,0.006643703,0.001711338,0.0009493555,0.003528791,0.0006448469],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005903309,0.0008764103,0.3734762,0.001432884,0.0004172826,0.01864706,0.006236118,0.0539958,0.02002898,0.1157687,0.07276548,0.3357647],"study_design_scores_gemma":[0.000174862,0.0003608525,0.06729061,0.001216621,0.0003997987,0.01692838,0.01227988,0.6932999,0.02356598,0.05951715,0.1247644,0.0002014723],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1281099,0.0005804315,0.8368061,0.004786471,0.0003514939,0.003697078,0.007154073,0.002609151,0.01590525],"genre_scores_gemma":[0.3165225,0.0002019592,0.6742058,0.0004343542,0.00007153594,0.0007266022,0.006261597,0.0001503717,0.001425249],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01218561,"threshold_uncertainty_score":0.02497756,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5272351720173516,"score_gpt":0.5090941169199376,"score_spread":0.01814105509741404,"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."}}