{"id":"W6889032915","doi":"10.25345/c5kn57","title":"MassIVE MSV000087016 - Plasma proteomics of ischemic and nonischemic cardiomyopathy patients","year":2021,"lang":"en","type":"dataset","venue":"UC San Diego","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Cardiomyopathy; Proteomics; Ischemic cardiomyopathy; Heart failure; Disease","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009556955,0.002025997,0.00234532,0.001853153,0.0006017318,0.001621222,0.002005895,0.002107359,0.02492146],"category_scores_gemma":[0.005826055,0.0005821965,0.001728256,0.00320485,0.0002814984,0.0005431364,0.001550878,0.0009991722,0.01670662],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000931096,"about_ca_system_score_gemma":0.001875955,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01873909,"about_ca_topic_score_gemma":0.02956907,"domain_scores_codex":[0.9990433,0.0001469045,0.0001338807,0.0003963864,0.0001490044,0.0001305807],"domain_scores_gemma":[0.9983443,0.0005823101,0.0002471774,0.0003382435,0.0003169012,0.0001709767],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001692786,0.00007615992,0.0164449,0.00166494,0.0006394813,0.0002163621,0.00003996792,0.0009090834,0.0004390206,0.0004383893,0.9683505,0.009088442],"study_design_scores_gemma":[0.006336601,0.0002730457,0.1250369,0.002101609,0.001568993,0.001425913,0.0002217216,0.003542379,0.001722835,0.005847162,0.8517614,0.0001614518],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.002217455,0.0004501309,0.0001350892,0.0001471577,0.00004234406,0.0000220488,0.9956813,0.0002509261,0.001053595],"genre_scores_gemma":[0.00430606,0.0002032352,0.0004482281,0.0001836935,0.00003338748,0.0001293449,0.9939375,0.00005553047,0.0007030238],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02492146,"threshold_uncertainty_score":0.08337063,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008343562151446039,"score_gpt":0.2241346602616521,"score_spread":0.2157910981102061,"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."}}