{"id":"W2986767149","doi":"10.1093/nar/gkz1009","title":"Exposome-Explorer 2.0: an update incorporating candidate dietary biomarkers and dietary associations with cancer risk","year":2019,"lang":"en","type":"article","venue":"Nucleic Acids Research","topic":"Health, Environment, Cognitive Aging","field":"Environmental Science","cited_by":78,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Centre International de Recherche sur le Cancer; World Health Organization","keywords":"Exposome; Biology; Nutrigenomics; Environmental health; Epidemiology; Environmental epidemiology; Cancer; Bioinformatics; Medicine; Internal medicine; Genetics","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":[0.009166032,0.002409115,0.003297945,0.01234968,0.0004193642,0.005007402,0.002774938,0.001618067,0.03164994],"category_scores_gemma":[0.01898078,0.00176732,0.002803544,0.008042708,0.0003579881,0.003252583,0.003469893,0.002136678,0.02199659],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006222975,"about_ca_system_score_gemma":0.002216286,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002058291,"about_ca_topic_score_gemma":0.004407255,"domain_scores_codex":[0.9959122,0.001159304,0.0008732735,0.0005113594,0.001362254,0.0001816504],"domain_scores_gemma":[0.9770563,0.01328183,0.002686595,0.00165932,0.003885712,0.001430175],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001619268,0.0001425591,0.01051429,0.01271374,0.001316324,0.0002994118,0.0002572598,0.0005933332,0.004241182,0.001273156,0.3959585,0.571071],"study_design_scores_gemma":[0.0001745688,0.0001048274,0.01190583,0.001861857,0.0007391157,0.0006497799,0.00003149691,0.0004783431,0.001436069,0.0009378315,0.9815554,0.000124879],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"software","genre_scores_codex":[0.01790536,0.2524575,0.06600878,0.01570828,0.005581963,0.001634963,0.5268467,0.07814334,0.03571313],"genre_scores_gemma":[0.02155495,0.1730745,0.1700354,0.01018708,0.007828079,0.00270413,0.5524434,0.02023996,0.04193255],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.03164994,"threshold_uncertainty_score":0.1058796,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04118782533587724,"score_gpt":0.3263036884830037,"score_spread":0.2851158631471265,"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."}}