{"id":"W56594587","doi":"10.1161/circ.118.suppl_18.s_779","title":"Abstract 2808: Combination of Adenosine Stress Perfusion and Late Enhancement Cardiac Magnetic Resonance Imaging in Patients with Suspected Coronary Artery Disease, Percutaneous Coronary Intervention and Coronary Bypass Graft -A Multi-Center Study","year":2008,"lang":"en","type":"article","venue":"Circulation","topic":"Cardiac Imaging and Diagnostics","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Medicine; Conventional PCI; Cardiology; Coronary artery disease; Percutaneous coronary intervention; Internal medicine; Fractional flow reserve; Stenosis; Perfusion; Radiology; Ischemia; Artery; Coronary arteries; Cardiac magnetic resonance imaging; Magnetic resonance imaging; Myocardial perfusion imaging; Stress testing (software); Myocardial infarction; Coronary angiography","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":[0.001482219,0.0008487323,0.0009132879,0.0006779963,0.0005796308,0.0008346937,0.0005543647,0.001150659,0.001872464],"category_scores_gemma":[0.002936926,0.0008809796,0.000888957,0.0006073756,0.0004348613,0.001021025,0.0005896369,0.0007751842,0.0005675401],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003158441,"about_ca_system_score_gemma":0.0003231123,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007558074,"about_ca_topic_score_gemma":0.0009753443,"domain_scores_codex":[0.9989102,0.0004227572,0.0001374413,0.0002650739,0.0001487059,0.000115817],"domain_scores_gemma":[0.9982827,0.0004840201,0.0004431065,0.000118014,0.0001496707,0.0005225137],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003562934,0.0004010714,0.994156,0.00002113481,0.000181261,0.000284571,0.00005732208,0.00004536933,0.000533923,0.000007925689,0.00006773899,0.0006807062],"study_design_scores_gemma":[0.0006500271,0.004485046,0.992026,0.0000154027,0.0002392312,0.001361269,0.0001680404,0.0006603183,0.0001608101,0.00002567519,0.000191506,0.00001668726],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9996418,0.0001114583,0.00003828586,0.00002345428,0.000007145802,0.00002129062,0.00005805257,0.000001324399,0.00009721465],"genre_scores_gemma":[0.9994611,0.00005673507,0.00008930686,0.00003629988,0.00004876993,0.00002546508,0.0002183821,0.000001719423,0.00006230463],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001872464,"threshold_uncertainty_score":0.007838786,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007967100718132865,"score_gpt":0.2294117231727066,"score_spread":0.2214446224545737,"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."}}