{"id":"W2533446135","doi":"10.1093/nar/gkw980","title":"Exposome-Explorer: a manually-curated database on biomarkers of exposure to dietary and environmental factors","year":2016,"lang":"en","type":"article","venue":"Nucleic Acids Research","topic":"Health, Environment, Cognitive Aging","field":"Environmental Science","cited_by":152,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"FP7 Food, Agriculture and Fisheries, Biotechnology; European Commission; World Health Organization","keywords":"Exposome; Biomonitoring; Biorepository; Biology; Environmental epidemiology; Biomarker; Biobank; Environmental health; Data science; Database; Bioinformatics; Computer science; Medicine; Ecology","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":[0.003198309,0.002866533,0.003365775,0.02713051,0.000798798,0.002883721,0.00238034,0.001807214,0.03684023],"category_scores_gemma":[0.01365106,0.001002674,0.002267367,0.02044177,0.0004780219,0.001924246,0.003878136,0.0011897,0.02427304],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000804187,"about_ca_system_score_gemma":0.003923822,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00370382,"about_ca_topic_score_gemma":0.006376808,"domain_scores_codex":[0.9970903,0.0004929202,0.0009340377,0.000751324,0.0005886027,0.0001427641],"domain_scores_gemma":[0.9893801,0.005559149,0.001966045,0.00117755,0.001375173,0.0005419904],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002291805,0.0002436215,0.02742741,0.1123798,0.00279271,0.003064716,0.001669919,0.003136825,0.03322032,0.007216237,0.6399513,0.1666054],"study_design_scores_gemma":[0.0001758428,0.00009581444,0.02394355,0.00264823,0.0008795325,0.0007476982,0.000158129,0.000597392,0.004751848,0.001905072,0.9639518,0.0001452225],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.002975625,0.003799526,0.004541506,0.0001381816,0.00007344218,0.0001538279,0.9801089,0.005314283,0.002894733],"genre_scores_gemma":[0.00597764,0.00288396,0.01478702,0.0001557177,0.00005788514,0.0006479686,0.9723493,0.001231995,0.001908503],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03684023,"threshold_uncertainty_score":0.1232429,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0638576445355641,"score_gpt":0.3251722743612152,"score_spread":0.2613146298256511,"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."}}