{"id":"W2996448489","doi":"10.1111/ctr.13765","title":"Biomarker discovery in cardiac allograft vasculopathy using targeted aptamer proteomics","year":2019,"lang":"en","type":"article","venue":"Clinical Transplantation","topic":"Transplantation: Methods and Outcomes","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Canadian Institutes of Health Research","keywords":"Biomarker; Medicine; Biomarker discovery; Receiver operating characteristic; Internal medicine; Proteomics; Area under the curve; Heart transplantation; Oncology; Cardiology; Transplantation; Bioinformatics; Pathology; Biology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001203466,0.0002029949,0.0006492411,0.0001634412,0.00003699572,0.00002883889,0.00007777047,0.0002497409,0.00005794506],"category_scores_gemma":[0.00005848686,0.0001714389,0.0004152232,0.0003100397,0.00008592153,0.0003044257,0.000005846255,0.0003400897,0.00004688215],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004214529,"about_ca_system_score_gemma":0.0001223532,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008997828,"about_ca_topic_score_gemma":0.00002143232,"domain_scores_codex":[0.997754,0.0003854288,0.00084087,0.0004564382,0.000276166,0.0002871198],"domain_scores_gemma":[0.9989194,0.0005192824,0.0001209796,0.0002687246,0.00005454116,0.0001170597],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001402939,0.0001754617,0.959794,0.0004699797,0.0001403288,0.00006983788,0.0003292947,0.0000727943,0.03445106,0.0001365545,0.00000504015,0.002952711],"study_design_scores_gemma":[0.005273023,0.0001765163,0.9885641,0.0003368018,0.0004074714,0.00002809426,0.00009845565,0.00124789,0.003320831,0.000119851,0.0001889273,0.0002380667],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9670911,0.0001704761,0.02994099,0.0001869192,0.00095102,0.001107179,0.00006729746,0.0000569181,0.000428083],"genre_scores_gemma":[0.9400561,0.001439353,0.05731141,0.0004147359,0.0001489029,0.00002591232,0.0003655216,0.0000392859,0.0001987114],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03113022,"threshold_uncertainty_score":0.6991075,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07673360685495352,"score_gpt":0.4024181663117748,"score_spread":0.3256845594568213,"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."}}