{"id":"W2091856956","doi":"10.3390/ijerph7114002","title":"An Assessment of the Interindividual Variability of Internal Dosimetry during Multi-Route Exposure to Drinking Water Contaminants","year":2010,"lang":"en","type":"article","venue":"International Journal of Environmental Research and Public Health","topic":"Effects and risks of endocrine disrupting chemicals","field":"Environmental Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Institut National de Santé Publique du Québec","funders":"Canadian Institutes of Health Research","keywords":"Ingestion; Internal dose; Percentile; Reference dose; Inhalation exposure; Dosimetry; Internal dosimetry; Absorbed dose; Inhalation; Contamination; Physiologically based pharmacokinetic modelling; Environmental science; Animal science; Toxicology; Environmental chemistry; Chemistry; Nuclear medicine; Mathematics; Pharmacokinetics; Medicine; Risk assessment; Radiochemistry; Statistics; Internal medicine; Biology; Anesthesia","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":[0.002537256,0.0003631243,0.0006038219,0.0004225921,0.0001932646,0.0007802626,0.0003235198,0.0004232938,0.0003637594],"category_scores_gemma":[0.004838324,0.0002308131,0.0005097533,0.0004472131,0.0002699737,0.0003230143,0.0004782216,0.0004050398,0.0001318089],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003556737,"about_ca_system_score_gemma":0.00024576,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00143772,"about_ca_topic_score_gemma":0.001391495,"domain_scores_codex":[0.9981425,0.0005534618,0.00008520449,0.0005422845,0.0006213067,0.00005525286],"domain_scores_gemma":[0.9962179,0.001823161,0.0007094687,0.00063946,0.0005588747,0.00005110426],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002355681,0.0002950725,0.4921897,0.0003293834,0.001546082,0.0003891689,0.001595367,0.04507933,0.3600485,0.0004416305,0.0004194698,0.0953107],"study_design_scores_gemma":[0.00002463485,0.003134351,0.8126886,0.00002925396,0.0004962904,0.001718973,0.0004636525,0.05897753,0.119348,0.0006167199,0.002396577,0.0001052987],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9586347,0.0005004695,0.0396237,0.00002181623,0.00001360894,0.00006085675,0.0002871227,0.00009902729,0.0007587366],"genre_scores_gemma":[0.9918738,0.0002106044,0.007055513,0.00002547818,0.000008831136,0.00004654789,0.0003360464,0.00006199449,0.0003811341],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002537256,"threshold_uncertainty_score":0.01341844,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02852392392352934,"score_gpt":0.4374536535638417,"score_spread":0.4089297296403124,"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."}}