{"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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002475784,0.0002340746,0.0002517278,0.0001393039,0.0007687967,0.0001101363,0.000355725,0.00012483,0.002399739],"category_scores_gemma":[0.000115251,0.0002016919,0.0000335251,0.0006287537,0.0006483673,0.001029906,0.0005450482,0.0008253328,0.0009948923],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006985415,"about_ca_system_score_gemma":0.00007846303,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009439901,"about_ca_topic_score_gemma":0.002538489,"domain_scores_codex":[0.9958791,0.0008035052,0.0002953019,0.0009684812,0.001161537,0.000892056],"domain_scores_gemma":[0.9985368,0.0002276873,0.0001604534,0.0006035844,0.00003314512,0.0004383922],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007574997,0.00007929842,0.9518697,0.00001430915,0.00006225982,0.00001706236,0.001351205,0.0002073275,0.008097083,0.00000490287,0.0003666198,0.03785443],"study_design_scores_gemma":[0.0006419825,0.0003715226,0.9916752,0.00004475759,0.00002113394,0.000002986224,0.001436135,0.003716365,0.0005198446,0.0003157569,0.0009553211,0.0002990016],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.993991,0.0000954945,0.00003133883,0.0008787083,0.00005426951,0.0008071485,0.0001360228,0.00005507427,0.003950965],"genre_scores_gemma":[0.9966685,0.0007501509,0.001727545,0.000353087,0.00005975784,0.0001187001,0.00007490309,0.00006358656,0.0001837986],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03980545,"threshold_uncertainty_score":0.9997829,"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."}}