{"id":"W2142573672","doi":"10.1021/es4051082","title":"New Insights into Traditional Health Risk Assessments of Mercury Exposure: Implications of Selenium","year":2013,"lang":"en","type":"article","venue":"Environmental Science & Technology","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":121,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"U.S. Food and Drug Administration","keywords":"Mercury (programming language); Selenium; MERCURY EXPOSURE; Risk assessment; Exposure assessment; Environmental chemistry; Reference dose; Toxicology; Environmental health; Chemistry; Medicine; Biology; Biomonitoring; Computer science","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":[],"category_scores_codex":[0.0002332607,0.0001524784,0.0002413031,0.0002415893,0.0003578138,0.000009405098,0.0005709089,0.00008030065,0.002426976],"category_scores_gemma":[0.00003234776,0.0001352749,0.00005062364,0.001026997,0.002537495,0.0005407023,0.0003380743,0.0001561845,0.000236506],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003732576,"about_ca_system_score_gemma":0.00007899816,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000705765,"about_ca_topic_score_gemma":0.00004045034,"domain_scores_codex":[0.9982696,0.00003720478,0.0004444743,0.000394384,0.0005148412,0.0003395587],"domain_scores_gemma":[0.9989738,0.00003713995,0.0003943942,0.0003970173,0.000006926546,0.0001906711],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.000002565216,0.0002225231,0.3120288,0.000004415285,0.00001498964,1.050406e-7,0.0009593048,0.00007074032,0.6093237,0.00183652,0.002117333,0.07341906],"study_design_scores_gemma":[0.0002648473,0.0004035241,0.8868586,0.000008301378,0.00001032799,0.000006375731,0.0009053669,0.00004199784,0.08866257,0.02043926,0.002246789,0.0001519992],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9929914,0.0002435091,0.002549904,0.001632518,0.00007943652,0.0003816698,0.0000194107,0.00003867589,0.002063517],"genre_scores_gemma":[0.9902538,0.0003177607,0.009108009,0.0001186024,0.00001115515,0.00004608108,0.000008270721,0.000007816477,0.000128523],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5748299,"threshold_uncertainty_score":0.998485,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0162368419186692,"score_gpt":0.2708336538850677,"score_spread":0.2545968119663986,"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."}}