{"id":"W4288428471","doi":"10.1101/2022.07.27.22276826","title":"Aptamer Proteomics for Biomarker Discovery in Heart Failure with Reduced Ejection Fraction","year":2022,"lang":"en","type":"preprint","venue":"medRxiv","topic":"GDF15 and Related Biomarkers","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Montreal Heart Institute","funders":"Relypsa; Novo Nordisk; University of Glasgow; Boston Scientific Corporation; Alnylam Pharmaceuticals; MyoKardia; Gilead Sciences; Cytokinetics; Daiichi Sankyo Europe; Sanofi; Bristol-Myers Squibb; AstraZeneca; Amgen; Pfizer; Ironwood Pharmaceuticals, Incorporated; GlaxoSmithKline","keywords":"Mendelian randomization; Biomarker; Clinical endpoint; Biomarker discovery; Heart failure; Internal medicine; Natriuretic peptide; Proteomics; Proportional hazards model; Medicine; Ejection fraction; Clinical trial; Oncology; Bioinformatics; Cardiology; Biology; Genetics; Genotype; Genetic variants","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005119772,0.0003079633,0.0004938972,0.0004163246,0.0001028975,0.00004670478,0.0001010683,0.0004800636,0.0001277582],"category_scores_gemma":[0.00009805575,0.0002369961,0.0002208026,0.0003527742,0.0000729518,0.0001100361,0.0001297073,0.001104094,0.000008298189],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003922037,"about_ca_system_score_gemma":0.0003263596,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001709347,"about_ca_topic_score_gemma":0.00004740564,"domain_scores_codex":[0.9981825,0.0001069512,0.0003801709,0.0006843726,0.0003355067,0.0003104627],"domain_scores_gemma":[0.9990724,0.0000556251,0.0002191887,0.0004854019,0.00007803839,0.00008940044],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.01110972,0.001043694,0.6870281,0.002145877,0.001276479,0.0001258817,0.0003333545,0.0004852711,0.2807916,0.00003445589,0.01444667,0.001178928],"study_design_scores_gemma":[0.01118444,0.001508567,0.8256916,0.002374127,0.00110723,0.0003335181,0.002152297,0.004132634,0.03203411,0.000445533,0.1175671,0.00146881],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9890622,0.0001313022,0.001121946,0.004906968,0.0009593339,0.003172396,0.0000322756,0.00009598287,0.0005175772],"genre_scores_gemma":[0.9904695,0.00006399152,0.005448689,0.0001850991,0.0001982438,0.00120687,0.0004770981,0.00008944593,0.001861066],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2487575,"threshold_uncertainty_score":0.966442,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0191585640723548,"score_gpt":0.2793461564436199,"score_spread":0.2601875923712652,"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."}}