{"id":"W4403226964","doi":"10.1016/j.cjca.2024.08.181","title":"MEDIUM TERM CARDIOVASCULAR OUTCOMES AND THEIR RELATIONSHIP WITH CARDIAC MAGNETIC RESONANCE IMAGING ABNORMALITIES IN PATIENTS PREVIOUSLY HOSPITALIZED WITH COVID-19","year":2024,"lang":"en","type":"article","venue":"Canadian Journal of Cardiology","topic":"Cardiac Imaging and Diagnostics","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Medicine; Coronavirus disease 2019 (COVID-19); Magnetic resonance imaging; Cardiac magnetic resonance; Term (time); Cardiac magnetic resonance imaging; 2019-20 coronavirus outbreak; Cardiology; Internal medicine; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Radiology; Pathology; Disease","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.0004939182,0.000329652,0.0005249998,0.0009904569,0.0008705172,0.001469487,0.0005329631,0.001009545,0.002591926],"category_scores_gemma":[0.003928414,0.0003089507,0.000799925,0.001251683,0.0004621425,0.001034767,0.0009090105,0.002472962,0.0003119962],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005824307,"about_ca_system_score_gemma":0.0007003733,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007732519,"about_ca_topic_score_gemma":0.01215806,"domain_scores_codex":[0.9993687,0.00009317093,0.00009500131,0.00009201558,0.0001193993,0.0002317904],"domain_scores_gemma":[0.9966232,0.0005427925,0.001334348,0.0001418585,0.0002637422,0.001094093],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009867055,0.00005378061,0.9991253,0.00000406458,0.00003625797,0.0001585853,0.00003696608,0.00001257667,0.00003533125,0.00001643382,0.00006700884,0.0003551362],"study_design_scores_gemma":[0.000004556987,0.000104407,0.998991,0.000009604044,0.00002158813,0.0003179064,0.0003350803,0.00007453309,0.00001272957,0.00003398192,0.00008767282,0.00000701886],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9981146,0.0004180083,0.00003863776,0.0001629616,0.00003507204,0.000006863699,0.0003727976,0.000002440833,0.0008486153],"genre_scores_gemma":[0.9988083,0.0001972026,0.00004285631,0.0000726498,0.00006774186,0.000008223899,0.0005972403,0.000001830257,0.0002039884],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007732519,"threshold_uncertainty_score":0.01537502,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00914184090322728,"score_gpt":0.2283858854687609,"score_spread":0.2192440445655336,"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."}}