{"id":"W3048186562","doi":"10.29173/hsi297","title":"Revealing obesity through diet-gene interactions","year":2020,"lang":"en","type":"article","venue":"Health Science Inquiry","topic":"Nutrition, Genetics, and Disease","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Obesity; Nutrigenomics; Disease; Intervention (counseling); Bioinformatics; Diabetes mellitus; Type 2 diabetes; Medicine; Fatty liver; Biology; Environmental health; Gene; Endocrinology; Genetics; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.001061272,0.000659868,0.0005514685,0.0009038171,0.0003947566,0.001237881,0.0003658867,0.0005852836,0.002885232],"category_scores_gemma":[0.001990841,0.0002187612,0.0007475516,0.001073017,0.0006468426,0.0006459311,0.0006464032,0.001041935,0.0002971922],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000413523,"about_ca_system_score_gemma":0.000647047,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002655743,"about_ca_topic_score_gemma":0.004680649,"domain_scores_codex":[0.9993725,0.0003057324,0.0000225297,0.0001527428,0.00007883753,0.00006767471],"domain_scores_gemma":[0.9991036,0.0005290976,0.000168333,0.00007848307,0.00004981604,0.00007075285],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00153826,0.0008478103,0.7448182,0.0009441705,0.004263683,0.001348711,0.0005767106,0.003655175,0.09037603,0.01411292,0.00313689,0.1343814],"study_design_scores_gemma":[0.00006844578,0.0006103358,0.9262713,0.0001830594,0.002197521,0.001000034,0.0006381003,0.008626211,0.009396567,0.03979662,0.01114304,0.00006869192],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.922577,0.01584641,0.04031558,0.007211871,0.0002932318,0.00008743767,0.003004757,0.0003254231,0.01033835],"genre_scores_gemma":[0.97092,0.008000664,0.01625709,0.001949853,0.0001200212,0.00008066498,0.0008091211,0.00005705707,0.001805489],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002885232,"threshold_uncertainty_score":0.009652019,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09442069087150373,"score_gpt":0.3800282861527042,"score_spread":0.2856075952812004,"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."}}