{"id":"W2140377493","doi":"10.1080/10976640600778049","title":"Characterization of Microvascular Dysfunction After Acute Myocardial Infarction by Cardiovascular Magnetic Resonance First-Pass Perfusion and Late Gadolinium Enhancement Imaging","year":2006,"lang":"en","type":"article","venue":"Journal of Cardiovascular Magnetic Resonance","topic":"Cardiac Imaging and Diagnostics","field":"Medicine","cited_by":64,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research","keywords":"Medicine; TIMI; Interquartile range; Cardiology; Myocardial infarction; Internal medicine; Perfusion; Angiology; Magnetic resonance imaging; Cardiac magnetic resonance imaging; Perfusion scanning; Myocardial perfusion imaging; Ejection fraction; Radiology; Percutaneous coronary intervention; Heart failure","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001582109,0.0004937823,0.001615819,0.0003628193,0.0001492727,0.00009496015,0.0001612344,0.0002027781,0.0000457844],"category_scores_gemma":[0.0001346475,0.0004720564,0.002495588,0.0004973553,0.0002751814,0.000357249,0.0001128075,0.0004901339,0.000009205382],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002068103,"about_ca_system_score_gemma":0.0001516125,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001988536,"about_ca_topic_score_gemma":0.000001784834,"domain_scores_codex":[0.995426,0.0003118794,0.001274479,0.0006319922,0.001814203,0.0005414318],"domain_scores_gemma":[0.9973943,0.00008340095,0.0003688756,0.0009415474,0.001003334,0.0002085698],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001986928,0.0004652957,0.07983389,0.0005856713,0.002306937,0.0009069853,0.0003420463,0.0004112629,0.09128267,0.000007468557,0.002434362,0.8194365],"study_design_scores_gemma":[0.004494254,0.0004725678,0.4765691,0.0005786875,0.00432935,0.001099159,0.00002035507,0.0003523719,0.009760012,0.00001743382,0.5019636,0.0003431751],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5430818,0.4518939,0.003545352,0.0002073114,0.0006039614,0.0004679894,0.0000291842,0.00002182485,0.0001486706],"genre_scores_gemma":[0.8615738,0.1343987,0.001783271,0.0002365148,0.00131974,0.00006820083,0.00006984621,0.0001119074,0.0004380442],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8190933,"threshold_uncertainty_score":0.9997731,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002817445105083231,"score_gpt":0.1871407705650361,"score_spread":0.1843233254599529,"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."}}