{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001154997,0.0004717714,0.0002986931,0.0006401537,0.0002659451,0.0005986454,0.0001779378,0.0003557903,0.001513009],"category_scores_gemma":[0.002390339,0.0001613937,0.000416223,0.0008128227,0.0003055169,0.0001949694,0.0004001056,0.0003398183,0.0001344137],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001842965,"about_ca_system_score_gemma":0.0003285307,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002595386,"about_ca_topic_score_gemma":0.002626783,"domain_scores_codex":[0.9996518,0.0001152774,0.0000287018,0.0001243908,0.00004530368,0.0000345414],"domain_scores_gemma":[0.9986603,0.0004704162,0.0005437319,0.0001194858,0.0001059311,0.0001001292],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008281721,0.00003285018,0.9891292,0.00008359805,0.0006546778,0.00008898133,0.00007347456,0.0001379143,0.003723482,0.00006026793,0.0000794983,0.005107871],"study_design_scores_gemma":[0.00001890461,0.0001704065,0.9981914,0.00001935399,0.000348899,0.0001972835,0.00004113461,0.0001994416,0.000396287,0.0001529663,0.0002600559,0.000003904664],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9957867,0.002611954,0.0005347601,0.0001394798,0.000007868907,0.000009900686,0.0005112786,0.000007099757,0.000390846],"genre_scores_gemma":[0.9982592,0.0005597465,0.0006377191,0.0000473798,0.00001392922,0.00001185563,0.0002795399,0.000002533122,0.0001879992],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002595386,"threshold_uncertainty_score":0.006108344,"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."}}