{"id":"W4403227428","doi":"10.1016/j.cjca.2024.08.043","title":"UNVEILING HIDDEN RISKS: ENHANCING DETECTION OF TOTALLY OCCLUDED ARTERIES IN NON-ST-ELEVATION MYOCARDIAL INFARCTION PATIENTS WITH ARTIFICAL INTELLIGENCE","year":2024,"lang":"en","type":"article","venue":"Canadian Journal of Cardiology","topic":"ECG Monitoring and Analysis","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Milton District Hospital","funders":"","keywords":"Medicine; Cardiology; Internal medicine; Myocardial infarction; Coronary arteries; Elevation (ballistics); Artery","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":[0.0008028108,0.000569692,0.0005068852,0.001145434,0.0001638327,0.001054064,0.0003921049,0.0008394751,0.0005495365],"category_scores_gemma":[0.003855219,0.0001855931,0.0004222134,0.000370927,0.000195062,0.0005352716,0.0005731581,0.0004920728,0.0001611229],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001075561,"about_ca_system_score_gemma":0.0001714227,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009778254,"about_ca_topic_score_gemma":0.001649556,"domain_scores_codex":[0.9997129,0.0001041041,0.00002698294,0.0000544717,0.00006598503,0.00003557674],"domain_scores_gemma":[0.9989228,0.000719393,0.0001004703,0.00005730282,0.0001322296,0.0000677787],"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":[0.003517575,0.0006860357,0.2785432,0.0005745821,0.0004289877,0.002714386,0.0006124102,0.03735266,0.0396093,0.00178659,0.00499999,0.6291742],"study_design_scores_gemma":[0.00009723704,0.001053279,0.2362246,0.0001357822,0.000642356,0.003836544,0.0005660426,0.7334507,0.01367339,0.007125537,0.003087506,0.0001070351],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8574801,0.003459073,0.1326388,0.001182592,0.0002265098,0.00008138224,0.0005973951,0.0005252151,0.003808907],"genre_scores_gemma":[0.9696921,0.0006393122,0.02879803,0.0001618532,0.0001390225,0.00001292929,0.0001825221,0.00001918869,0.0003550161],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001145434,"threshold_uncertainty_score":0.004245758,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01542543780586157,"score_gpt":0.2584270585145234,"score_spread":0.2430016207086619,"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."}}