{"id":"W2967758975","doi":"10.1161/circgen.118.002384","title":"Lipidomics, Atrial Conduction, and Body Mass Index","year":2019,"lang":"en","type":"article","venue":"Circulation Genomic and Precision Medicine","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre for Global Health Research","funders":"U.S. National Library of Medicine; Medical Research Council; Versus Arthritis","keywords":"Lipidomics; Body mass index; Index (typography); Cardiology; Internal medicine; Medicine; Chemistry; Computer science; Biochemistry; World Wide Web","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":[0.00037636,0.0001242745,0.000223649,0.00008097587,0.0000804581,0.00001502868,0.0000550199,0.0001101249,0.0001330361],"category_scores_gemma":[0.0001177326,0.0001029458,0.00003607185,0.00006087123,0.0000921323,0.000005901772,0.00006542759,0.00006922984,0.000009228301],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001040943,"about_ca_system_score_gemma":0.00001990531,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001229492,"about_ca_topic_score_gemma":0.000001735353,"domain_scores_codex":[0.9991453,0.00004354693,0.0002424274,0.0003430579,0.0001015622,0.000124075],"domain_scores_gemma":[0.9995266,0.00003466792,0.0001003746,0.0001992188,0.0000631259,0.00007602841],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0001610319,0.0000050381,0.1167901,0.00001616612,0.00007628452,2.731181e-7,0.00006248166,0.00008031588,0.8747563,0.0008359239,0.001015766,0.006200274],"study_design_scores_gemma":[0.007176491,0.0006075772,0.7715964,0.00004016983,0.0001321275,0.00005749858,0.0005386691,0.002412362,0.003270779,0.005895673,0.2077826,0.0004895739],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9873667,0.006157383,0.004122764,0.0003747935,0.0008417452,0.000264351,0.000005030963,0.000007364734,0.0008598242],"genre_scores_gemma":[0.9944609,0.003447593,0.0002634613,0.0001632343,0.0008967969,0.000002749517,0.0000546869,0.00001247582,0.0006980338],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8714855,"threshold_uncertainty_score":0.4198006,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01026859426502293,"score_gpt":0.2475455783269016,"score_spread":0.2372769840618787,"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."}}