{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002253879,0.0001038745,0.0001123704,0.00002790793,0.0004466457,0.00004278634,0.0002735882,0.00003779244,0.00002241466],"category_scores_gemma":[0.0001286443,0.0001075436,0.00005537383,0.0002856775,0.0004209599,0.00001727454,0.0001379812,0.00008307356,0.00002964103],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000343567,"about_ca_system_score_gemma":0.0005686982,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000362765,"about_ca_topic_score_gemma":0.00001172291,"domain_scores_codex":[0.9986889,0.00002928861,0.0002323685,0.0004794784,0.00020939,0.0003605357],"domain_scores_gemma":[0.9990916,0.000005331754,0.00008914142,0.0002820391,0.0001242008,0.0004076743],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005239936,0.0006260311,0.03151658,0.0004428609,0.00002502161,0.00001266046,0.00619262,0.0003928279,0.8703995,0.0007422508,0.0848883,0.004237338],"study_design_scores_gemma":[0.002207966,0.003315191,0.08229715,0.0001613959,0.0000351722,0.00005710917,0.005006995,0.0009591252,0.624527,0.001769462,0.2784161,0.001247342],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9838789,0.001698927,0.006870371,0.006008812,0.0008183867,0.0002207271,0.00002401808,0.00003431136,0.0004455197],"genre_scores_gemma":[0.982833,0.0006752141,0.00395691,0.01133862,0.001082638,0.00001242026,0.00004794769,0.000009744587,0.00004345148],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2458725,"threshold_uncertainty_score":0.43855,"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."}}