{"id":"W4389489702","doi":"10.1111/petr.14652","title":"Cardiac magnetic resonance imaging in detection of progressive graft dysfunction in pediatric heart transplantation","year":2023,"lang":"en","type":"article","venue":"Pediatric Transplantation","topic":"Transplantation: Methods and Outcomes","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Heart, Lung, and Blood Institute; Circle Cardiovascular Imaging; National Institutes of Health; Siemens Healthineers","keywords":"Medicine; Magnetic resonance imaging; Cardiology; Fibrosis; Endomyocardial biopsy; Internal medicine; Cardiac magnetic resonance imaging; Heart transplantation; Transplantation; Heart failure; Cardiac magnetic resonance; Microvessel; Biopsy; Cardiac allograft vasculopathy; Retrospective cohort study; Cardiac fibrosis; Endomyocardial fibrosis; Radiology; Immunohistochemistry","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":[0.0007270077,0.0002538827,0.0004499858,0.001586266,0.00006153608,0.00001662531,0.00007287855,0.0001532799,0.00001777614],"category_scores_gemma":[0.00004061538,0.0002628347,0.0001523499,0.002649333,0.00003555124,0.0003323244,0.000003742858,0.0002952718,0.00002579841],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008605732,"about_ca_system_score_gemma":0.0001179163,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000264962,"about_ca_topic_score_gemma":0.0002111494,"domain_scores_codex":[0.9975317,0.0002465631,0.0008188937,0.0004752961,0.0005082515,0.0004193477],"domain_scores_gemma":[0.9991127,0.0003668386,0.0001562839,0.0001751944,0.0000996758,0.0000893125],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009552758,0.00009253633,0.9792641,0.001830967,0.000002869829,0.0002080868,0.001991919,0.0002217371,0.004530521,0.00002350849,0.00001059503,0.01086791],"study_design_scores_gemma":[0.003869416,0.0001872288,0.9904751,0.0001094406,0.0005123468,0.00007011691,0.0001096983,0.0006043306,0.003694356,0.0001108983,0.00002642112,0.0002307144],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9912164,0.004635698,0.002031595,0.0002088069,0.0005539898,0.0009627969,0.00009476253,0.000173554,0.000122446],"genre_scores_gemma":[0.9615817,0.03613418,0.001333601,0.00003876556,0.0003210684,0.000167314,0.0003505963,0.00003978877,0.00003299485],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03149848,"threshold_uncertainty_score":0.9999824,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01163196042083554,"score_gpt":0.2795812511017052,"score_spread":0.2679492906808696,"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."}}