{"id":"W2026097600","doi":"10.1161/circresaha.114.305675","title":"Targeting MicroRNAs to Limit Myocardial Lipid Accumulation","year":2015,"lang":"en","type":"letter","venue":"Circulation Research","topic":"Metabolism, Diabetes, and Cancer","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Canadian Institutes of Health Research","keywords":"microRNA; Lipid metabolism; Limit (mathematics); Lipid accumulation; Cardiology; Medicine; Chemistry; Cell biology; Biology; Internal medicine; Biochemistry; Gene; Mathematics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001750635,0.0002803068,0.0003235167,0.0003310904,0.0002018874,0.0001876454,0.0004508194,0.001066657,0.0001433227],"category_scores_gemma":[0.00088073,0.0003020284,0.000168365,0.0003842189,0.00008835814,0.00001001201,0.0002620819,0.001070327,0.0004205917],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001476777,"about_ca_system_score_gemma":0.0005223888,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006806866,"about_ca_topic_score_gemma":0.000009038195,"domain_scores_codex":[0.9962685,0.000606123,0.0003885648,0.0008402371,0.001120644,0.0007760082],"domain_scores_gemma":[0.9975941,0.00005820596,0.000116386,0.0007316505,0.001304554,0.0001951429],"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":[0.00003026006,0.0000111813,0.0004303061,0.00005769108,0.00006694946,0.000005953802,0.00007075177,0.001618857,0.0228864,0.000003891673,0.9599365,0.01488123],"study_design_scores_gemma":[0.0003233629,0.00006400461,0.0006957156,0.00002889758,0.00002036757,0.000001982118,0.00002178045,0.0001961217,0.00217853,0.0001045824,0.9960216,0.0003430078],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"commentary","genre_scores_codex":[0.4164526,0.3341662,0.005820323,0.2041481,0.0114456,0.008265253,0.0008002041,0.0002896872,0.01861201],"genre_scores_gemma":[0.2395619,0.01399729,0.001289283,0.5332174,0.1744704,0.001101944,0.02572368,0.0007290115,0.00990905],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.3290693,"threshold_uncertainty_score":0.9999432,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1335840259905225,"score_gpt":0.3929610800874722,"score_spread":0.2593770540969497,"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."}}