{"id":"W3013136118","doi":"10.3390/metabo10040123","title":"An Integrative Approach to Assessing Diet–Cancer Relationships","year":2020,"lang":"en","type":"review","venue":"Metabolites","topic":"Nutrition, Genetics, and Disease","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Canadian Cancer Society Research Institute; Michael Smith Health Research BC","keywords":"Omics; Cancer; Consistency (knowledge bases); Skepticism; Metabolomics; Metagenomics; Biomarker discovery; Data science; Bioinformatics; Biology; Proteomics; Medicine; Computational biology; Computer science; Genetics","routes":{"ca_aff":true,"ca_fund":true,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001829057,0.0004197898,0.0008482971,0.0001030519,0.0001502373,0.0001514043,0.0003569979,0.0002953831,0.00001722457],"category_scores_gemma":[0.000283073,0.0003415385,0.0003743409,0.0002976734,0.00006334941,0.000009035148,0.00009559363,0.0002594031,0.00002409077],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002305069,"about_ca_system_score_gemma":0.0003420379,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006280845,"about_ca_topic_score_gemma":0.000003677435,"domain_scores_codex":[0.9979512,0.0004931634,0.0003971225,0.0007489701,0.0001538265,0.000255704],"domain_scores_gemma":[0.998809,0.00002901027,0.0001672931,0.0005103177,0.0001292769,0.000355071],"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":[0.00006526495,0.0005502978,0.0002489113,0.005178995,0.0005342903,0.000003550958,0.000302534,0.00001651452,0.001267379,0.001066494,0.005218604,0.9855472],"study_design_scores_gemma":[0.0001183764,0.00007662497,0.00007757718,0.0005865526,0.0006798753,0.000002503664,0.0001351608,0.000008060656,0.0003099829,0.0001032629,0.9974899,0.0004121134],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00009438642,0.9933537,0.003802784,0.00002656969,0.0001952176,0.000589639,0.0003777228,0.00002926684,0.00153077],"genre_scores_gemma":[0.0003665982,0.986777,0.008199907,0.000172982,0.001453783,0.0004373381,0.002266415,0.00007333281,0.000252627],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9922713,"threshold_uncertainty_score":0.9999037,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06738549088556987,"score_gpt":0.3729211265673779,"score_spread":0.305535635681808,"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."}}