{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004006768,0.001322787,0.002226807,0.00511023,0.0003941459,0.002334528,0.001673575,0.001946488,0.003373249],"category_scores_gemma":[0.003307489,0.0003585806,0.00113154,0.003582959,0.001074322,0.002237753,0.001499361,0.002985591,0.001865163],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001746043,"about_ca_system_score_gemma":0.003356695,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003086652,"about_ca_topic_score_gemma":0.005542953,"domain_scores_codex":[0.9990265,0.0003886641,0.000102359,0.0001608189,0.0002837154,0.00003803274],"domain_scores_gemma":[0.9975859,0.001545384,0.0001554913,0.0000702646,0.0005599197,0.00008297626],"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":[0.00005566822,0.00006891555,0.0006169995,0.02115829,0.0004609555,0.0002202565,0.0001838011,0.0005512678,0.001879755,0.01987848,0.01777677,0.9371487],"study_design_scores_gemma":[0.0000187654,0.0001770746,0.003209873,0.01404332,0.0006556972,0.001775401,0.0003988573,0.0004357301,0.001240721,0.02499801,0.9529697,0.00007685052],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001920155,0.9900379,0.003642686,0.001972675,0.0004785814,0.00003010571,0.00009198906,0.00003006623,0.003524019],"genre_scores_gemma":[0.001808818,0.9896944,0.005945118,0.0009312806,0.0003285621,0.00004341586,0.00012046,0.00000906664,0.001118924],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.00511023,"threshold_uncertainty_score":0.02119011,"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."}}