{"id":"W3051748260","doi":"10.1016/j.yjmcc.2020.08.008","title":"Longitudinal correlation of biomarkers of cardiac injury, inflammation, and coagulation to outcome in hospitalized COVID-19 patients","year":2020,"lang":"en","type":"article","venue":"Journal of Molecular and Cellular Cardiology","topic":"COVID-19 Clinical Research Studies","field":"Medicine","cited_by":78,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"National Heart, Lung, and Blood Institute; Bristol-Myers Squibb Canada; National Institutes of Health; Takeda Pharmaceutical Company; GlaxoSmithKline Australia; Chinese Academy of Engineering; Chinese Academy of Sciences; AstraZeneca","keywords":"Medicine; Internal medicine; Fibrinogen; Troponin; Cardiology; Troponin I; Septic shock; Systemic inflammation; Inflammation; Sepsis; D-dimer; Gastroenterology; Myocardial infarction","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.000842366,0.00009913441,0.0007780379,0.0002152105,0.00001947571,0.000003467076,0.0000517649,0.00009963918,0.000003729885],"category_scores_gemma":[0.01160439,0.000084199,0.0001802958,0.0002273528,0.0001443993,0.00004383646,0.00008892895,0.0001594386,3.858048e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006038975,"about_ca_system_score_gemma":0.0001311536,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002377913,"about_ca_topic_score_gemma":4.520823e-7,"domain_scores_codex":[0.998337,0.0002587176,0.0008017058,0.0001546855,0.0003278097,0.0001201134],"domain_scores_gemma":[0.998531,0.0004108328,0.0003388081,0.00009855315,0.0003551542,0.0002656618],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001179951,0.00001985442,0.9476777,0.0003186252,0.0003108093,0.00004839311,0.000277658,0.0008074663,0.04784967,0.0000304927,0.00006566278,0.001413735],"study_design_scores_gemma":[0.002825499,0.002256963,0.9875537,0.00005902023,0.0002729013,0.000003766153,0.0000961711,0.0003364609,0.005714563,0.0001755159,0.000611048,0.00009439127],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9841239,0.0005887788,0.01210396,0.002732498,0.00007247335,0.0003382604,0.0000106325,0.000002541086,0.00002696926],"genre_scores_gemma":[0.999245,0.0002066366,0.000262687,0.0002206157,0.00004328573,0.000002653039,0.000009920862,0.000007281282,0.000001951586],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04213511,"threshold_uncertainty_score":0.9967213,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03043734942680203,"score_gpt":0.3537154309674905,"score_spread":0.3232780815406885,"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."}}