{"id":"W3001893346","doi":"10.1002/ejhf.1811","title":"A Network Analysis to Identify Pathophysiological Pathways Distinguishing Ischaemic from Non-Ischaemic Heart Failure","year":2020,"lang":"en","type":"article","venue":"European Journal of Heart Failure","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"Surgical Specialties (Canada)","funders":"National Medical Research Council; Vifor Pharma; National Institute for Health and Care Research; AstraZeneca; MyoKardia; Medical Research Council; Cytokinetics; Boston Scientific Corporation; Servier; European Commission; Amgen","keywords":"Medicine; Heart failure; Internal medicine; Pathophysiology; Myocardial infarction; Cardiology; Inflammation; Bioinformatics; Biology","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007671844,0.0003186344,0.0006216434,0.00007534315,0.0001846179,0.0001505499,0.0005811006,0.0001299643,0.00006525078],"category_scores_gemma":[0.0002039515,0.0002670389,0.0005694312,0.0004684723,0.00007219608,0.00001938233,0.0004377523,0.0006278441,0.0001214667],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001608698,"about_ca_system_score_gemma":0.00006669523,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004704294,"about_ca_topic_score_gemma":0.000009648533,"domain_scores_codex":[0.997604,0.0003469858,0.0008820687,0.0004047247,0.0002849755,0.0004772164],"domain_scores_gemma":[0.9984312,0.00003885116,0.0004020665,0.0003968117,0.0001915689,0.0005395162],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002379474,0.0000372889,0.003397841,0.00001560882,0.0006112483,0.000108444,0.0007074355,0.01710728,0.5341104,0.00001455648,0.4429717,0.0006802988],"study_design_scores_gemma":[0.002156723,0.002718807,0.03011136,0.0002894775,0.0008812009,0.0001891274,0.001338168,0.002824421,0.005960615,0.0002848725,0.9518844,0.001360839],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9397075,0.0006952768,0.04819586,0.01071481,0.0003010678,0.0001900404,0.0000700009,0.00002093669,0.0001045183],"genre_scores_gemma":[0.9368713,0.00002304629,0.05299689,0.006203726,0.003730435,0.00000150393,0.0001113584,0.0000456398,0.00001611298],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5281498,"threshold_uncertainty_score":0.9999782,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0142111787513062,"score_gpt":0.2346440938431402,"score_spread":0.220432915091834,"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."}}