{"id":"W2018571487","doi":"10.1371/journal.pone.0102570","title":"Use of Physiologically-Based Pharmacokinetic Modeling to Simulate the Profiles of 3-Hydroxybenzo(a)pyrene in Workers Exposed to Polycyclic Aromatic Hydrocarbons","year":2014,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Pesticide Exposure and Toxicity","field":"Agricultural and Biological Sciences","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Agence Nationale de Sécurité Sanitaire de l’Alimentation, de l’Environnement et du Travail","keywords":"Physiologically based pharmacokinetic modelling; Toxicokinetics; Pyrene; Inhalation exposure; Metabolite; Environmental chemistry; Chemistry; Inhalation; Urine; Pharmacokinetics; Xenobiotic; Exposure assessment; Benzo(a)pyrene; Toxicology; Pharmacology; Toxicity; Organic chemistry; Biology; Statistics; Biochemistry; Mathematics","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":[0.000385784,0.0005563585,0.0004277285,0.0002164165,0.0002034146,0.0005180484,0.0005006665,0.0008928822,0.000564665],"category_scores_gemma":[0.0011616,0.0002940928,0.0008429857,0.0001808985,0.0002311132,0.000302037,0.0002625172,0.0005956063,0.00014863],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000531743,"about_ca_system_score_gemma":0.0008972808,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008301175,"about_ca_topic_score_gemma":0.004032472,"domain_scores_codex":[0.9998376,0.00008367644,0.000008566914,0.00003202913,0.00002483372,0.00001320501],"domain_scores_gemma":[0.9995944,0.0002737952,0.00005641361,0.00002179028,0.00004155952,0.00001214401],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003495351,0.00003846635,0.001168175,0.00002477603,0.00002503184,0.00005169262,0.00002365429,0.9921622,0.003620035,0.0004665573,0.0000475759,0.002336939],"study_design_scores_gemma":[0.000011694,0.00009449808,0.0006741919,0.000003904246,0.00002092885,0.00003410123,0.000009372751,0.9965837,0.001652809,0.0005756399,0.0003298565,0.000009239997],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5434413,0.0005892313,0.4510259,0.0003671546,0.00005480352,0.0001828616,0.0005017148,0.0002926843,0.003544422],"genre_scores_gemma":[0.9698641,0.0004137052,0.02794149,0.00005375112,0.00001251625,0.0002095847,0.0002229176,0.00002343841,0.001258501],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008301175,"threshold_uncertainty_score":0.01650572,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07983538809573931,"score_gpt":0.2389853305784179,"score_spread":0.1591499424826786,"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."}}