{"id":"W2073753218","doi":"10.1016/j.jelectrocard.2003.09.013","title":"Computer classification algorithm for strictly posterior myocardial infarction","year":2003,"lang":"en","type":"article","venue":"Journal of Electrocardiology","topic":"Acute Myocardial Infarction Research","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Myocardial infarction; Computer science; Cardiology; Algorithm; Internal medicine; Medicine; Artificial intelligence; Pattern recognition (psychology)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009784428,0.0005710546,0.0008625655,0.001616695,0.000678431,0.001431026,0.00115216,0.00115706,0.00654162],"category_scores_gemma":[0.003612117,0.0002820892,0.0005368144,0.0006812912,0.0001877124,0.0006692899,0.0008527564,0.0007391809,0.002694704],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004942126,"about_ca_system_score_gemma":0.001241022,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004592811,"about_ca_topic_score_gemma":0.005994667,"domain_scores_codex":[0.9995611,0.00006533511,0.00006170949,0.0001195224,0.0001345032,0.00005775968],"domain_scores_gemma":[0.9986959,0.00053988,0.00005334124,0.0001058087,0.0005533036,0.00005174795],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000515255,0.0001724835,0.008029716,0.00005858971,0.00006101083,0.0001418808,0.00004825534,0.02106111,0.008457812,0.003083353,0.01055791,0.9478126],"study_design_scores_gemma":[0.0000799314,0.0001115272,0.004543468,0.00002267716,0.00006274995,0.0003484465,0.00003089652,0.9808881,0.005349234,0.00432391,0.004220759,0.00001828227],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04627654,0.0005174745,0.9451976,0.000392579,0.0002035768,0.0002686415,0.0005583327,0.003796103,0.002789221],"genre_scores_gemma":[0.269972,0.0003686603,0.716965,0.0003143527,0.0002516506,0.0005582506,0.002016393,0.0002284889,0.009325327],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00654162,"threshold_uncertainty_score":0.02188385,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02845945767199339,"score_gpt":0.3197616918389405,"score_spread":0.2913022341669471,"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."}}