{"id":"W4389945280","doi":"10.1161/circ.148.suppl_1.18770","title":"Abstract 18770: Understanding Patients’ Characteristics and Coronary Microvasculature: Early Insights From First US Coronary Microvascular Dysfunction Registry","year":2023,"lang":"en","type":"article","venue":"Circulation","topic":"Cardiac Imaging and Diagnostics","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Fractional flow reserve; Coronary flow reserve; Coronary artery disease; Cardiology; Internal medicine; Angina; Hemodynamics; Canadian Cardiovascular Society; Microcirculation; Coronary angiography; Myocardial infarction","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001754368,0.0002139861,0.0002798281,0.001203165,0.0002461561,0.000746248,0.0004486608,0.0004540058,0.001623361],"category_scores_gemma":[0.004642084,0.0001516073,0.0001958466,0.00140767,0.0001640068,0.0009276487,0.0007030593,0.0006152915,0.0004826491],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003217879,"about_ca_system_score_gemma":0.0005172683,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002290071,"about_ca_topic_score_gemma":0.004132458,"domain_scores_codex":[0.9995688,0.000161097,0.00005529436,0.00007175029,0.00007636132,0.00006674304],"domain_scores_gemma":[0.9975198,0.000669077,0.0009330002,0.0001733194,0.0002492519,0.0004555496],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005899339,0.00005306189,0.9933728,0.000013959,0.00001066463,0.00008227969,0.00007954123,0.00004386137,0.0001936973,0.00003162872,0.0005633912,0.005496063],"study_design_scores_gemma":[0.000007548445,0.00006023994,0.9984559,0.00001568297,0.0000131565,0.0002715285,0.0001384655,0.0002292521,0.0001091327,0.00004779654,0.000646271,0.000005026115],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9924796,0.0007517234,0.0004670097,0.0008349221,0.00001416942,0.00005672558,0.003413668,0.00003735495,0.001944839],"genre_scores_gemma":[0.9930224,0.0005428864,0.001580316,0.0002785199,0.00008628983,0.00006228175,0.004074687,0.00001040636,0.0003422814],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002290071,"threshold_uncertainty_score":0.009278119,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01950322545809463,"score_gpt":0.2195704922158066,"score_spread":0.2000672667577119,"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."}}