{"id":"W4401422081","doi":"10.32920/26520820.v1","title":"Plasma Metabolite Profiles Associated with the Amount and Source of Meat and Fish Consumption and the Risk of Type 2 Diabetes","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Nutritional Studies and Diet","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Instituto de Salud Carlos III; Canadian Institutes of Health Research; Centro Nacional de Investigaciones Cardiovasculares; Ministerio de Ciencia e Innovación; European Regional Development Fund; Generalitat Valenciana; National Institutes of Health; Ministerio de Economía y Competitividad; Institució Catalana de Recerca i Estudis Avançats; Ministerio de Ciencia, Innovación y Universidades","keywords":"Metabolite; Fish <Actinopterygii>; Type 2 diabetes; Consumption (sociology); Food science; Fish consumption; Chemistry; Diabetes mellitus; Fishery; Biology; Endocrinology; Biochemistry","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005897144,0.0003050382,0.0003702251,0.0002020834,0.0001531277,0.0004749729,0.0001332734,0.0003573839,0.002698956],"category_scores_gemma":[0.001386805,0.0003109109,0.000537731,0.000477187,0.0001158068,0.0002540966,0.0002363417,0.0004631902,0.0002302532],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001378201,"about_ca_system_score_gemma":0.0001290395,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008936496,"about_ca_topic_score_gemma":0.0008215691,"domain_scores_codex":[0.9998272,0.00006277947,0.00001563743,0.00004769878,0.00002673565,0.00002004756],"domain_scores_gemma":[0.9994549,0.0001596393,0.0002109024,0.00007216344,0.00004487007,0.00005742046],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.02777082,0.0002117563,0.9425349,0.0001475593,0.001539004,0.0001648898,0.00004995739,0.0005130098,0.01147106,0.00007277443,0.0009691344,0.01455509],"study_design_scores_gemma":[0.000204504,0.0007224912,0.9963261,0.00001390203,0.0004824196,0.0002169036,0.0000272568,0.0006358114,0.000753362,0.0001037602,0.0005032969,0.00001004347],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.995392,0.001135484,0.0005687851,0.00008124724,0.00002555802,0.000023729,0.001945516,0.00001746256,0.0008103282],"genre_scores_gemma":[0.9968022,0.0002317486,0.0004724012,0.00007897831,0.00002800285,0.00004005916,0.001330106,0.00001091246,0.001005551],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002698956,"threshold_uncertainty_score":0.009028912,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01412363531470857,"score_gpt":0.2382458204488056,"score_spread":0.2241221851340971,"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."}}