{"id":"W4324139839","doi":"10.1161/circ.147.suppl_1.p621","title":"Abstract P621: Visceral Adipose Tissue Attenuation: A Marker of Liver Fat Content Beyond the Body Mass Index and Visceral Adipose Tissue Area","year":2023,"lang":"en","type":"article","venue":"Circulation","topic":"Liver Disease Diagnosis and Treatment","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal; Centre Intégré Universitaire de Santé et de Services Sociaux du Saguenay–Lac-Saint-Jean; Centres Intégré Universitaires de Santé et de Services Sociaux; Institut universitaire de cardiologie et de pneumologie de Québec","funders":"","keywords":"Adipose tissue; Medicine; Body mass index; Fatty liver; Attenuation; Internal medicine; Adipocyte; Endocrinology; Intra-Abdominal Fat; White adipose tissue; Obesity; Pathology; Insulin resistance; Visceral fat","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":[0.00088482,0.0008820136,0.0006774903,0.0009390201,0.0002554379,0.0009715668,0.0006326498,0.0004801196,0.008224748],"category_scores_gemma":[0.002148305,0.0002862176,0.0003448251,0.001108518,0.0004018264,0.0005414282,0.0005831898,0.0007436231,0.001264521],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001846967,"about_ca_system_score_gemma":0.0002177549,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007727053,"about_ca_topic_score_gemma":0.0007531382,"domain_scores_codex":[0.9996,0.0001190706,0.00003915295,0.000102935,0.000114888,0.00002391625],"domain_scores_gemma":[0.9986438,0.0002340346,0.0008186768,0.00007793273,0.0001309521,0.00009458674],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004112606,0.0002169968,0.9220124,0.0006889486,0.00060122,0.0003888091,0.0001774901,0.001217771,0.01947912,0.000367002,0.004476734,0.04626087],"study_design_scores_gemma":[0.0001008788,0.0006649139,0.9873503,0.00008122045,0.0002233076,0.001292262,0.00007502157,0.003319067,0.002808427,0.0005056474,0.003559839,0.00001909307],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9738944,0.00523352,0.009109881,0.0005936862,0.0001100035,0.0001484901,0.0053661,0.0002812944,0.005262673],"genre_scores_gemma":[0.9869032,0.0006691085,0.005304251,0.0001228974,0.0001265332,0.0001761316,0.002283304,0.00005504573,0.004359467],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008224748,"threshold_uncertainty_score":0.02751458,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03373234150750488,"score_gpt":0.2771226079668318,"score_spread":0.2433902664593269,"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."}}