{"id":"W2736565862","doi":"10.1289/ehp1011","title":"The Saliva Exposome for Monitoring of Individuals’ Health Trajectories","year":2017,"lang":"en","type":"article","venue":"Environmental Health Perspectives","topic":"Health, Environment, Cognitive Aging","field":"Environmental Science","cited_by":60,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"National Institute of Environmental Health Sciences; National Cancer Institute","keywords":"Exposome; Saliva; Metabolome; Physiology; Biomarker; Biology; Metabolomics; Medicine; Bioinformatics; Computational biology; Genetics; Biochemistry","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":[0.001146465,0.0007033706,0.0007478502,0.007264765,0.0003466678,0.001335219,0.0004019708,0.0005227831,0.005178398],"category_scores_gemma":[0.004220533,0.0001851749,0.0009728608,0.006369147,0.0001917362,0.0009836691,0.001134669,0.0004608799,0.001311577],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003929922,"about_ca_system_score_gemma":0.0008707755,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00168631,"about_ca_topic_score_gemma":0.003609796,"domain_scores_codex":[0.9994067,0.0001941595,0.00007491707,0.0001913226,0.0001010256,0.0000318557],"domain_scores_gemma":[0.9976091,0.001126984,0.0006487366,0.0002312043,0.0002847884,0.000099141],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.002178966,0.0002795935,0.440185,0.01899368,0.00367335,0.000899851,0.001048652,0.007208366,0.04595198,0.005243878,0.03063357,0.4437031],"study_design_scores_gemma":[0.0001124535,0.0007671595,0.7315327,0.003018031,0.00288378,0.001966437,0.001945632,0.01593649,0.01543002,0.03028889,0.1959461,0.0001723267],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.3982632,0.07934359,0.0672047,0.003404421,0.0003582578,0.0007366237,0.4330857,0.002378366,0.01522521],"genre_scores_gemma":[0.7062891,0.03406138,0.1000383,0.0009779738,0.0003220002,0.0009852701,0.1548609,0.0002388579,0.002226326],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007264765,"threshold_uncertainty_score":0.01732343,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03191909296662054,"score_gpt":0.33421551692785,"score_spread":0.3022964239612295,"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."}}