{"id":"W2059170994","doi":"10.1080/15287394.2014.971477","title":"Assessing Human Variability in Kinetics for Exposures to Multiple Environmental Chemicals: A Physiologically Based Pharmacokinetic Modeling Case Study with Dichloromethane, Benzene, Toluene, Ethylbenzene, and<i>m</i>-Xylene","year":2015,"lang":"en","type":"article","venue":"Journal of Toxicology and Environmental Health","topic":"Carcinogens and Genotoxicity Assessment","field":"Biochemistry, Genetics and Molecular Biology","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de Santé Publique du Québec; Université de Montréal","funders":"","keywords":"Toxicokinetics; Inhalation; Inhalation exposure; Chemistry; Toluene; Dichloromethane; Benzene; Pharmacokinetics; Ethylbenzene; Coefficient of variation; Cmax; Environmental chemistry; Chromatography; Toxicity; Pharmacology; Medicine; Organic chemistry; Anesthesia","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":[0.001386766,0.0004616855,0.0004953404,0.0002356462,0.0001864543,0.0008529546,0.0005236831,0.0007354873,0.0004466927],"category_scores_gemma":[0.002908202,0.0002715605,0.0007961748,0.0002697146,0.0002137705,0.0002789345,0.0003412089,0.0004855962,0.0001152401],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00060671,"about_ca_system_score_gemma":0.0007460922,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007709357,"about_ca_topic_score_gemma":0.003890575,"domain_scores_codex":[0.9993886,0.0003192874,0.0000220032,0.0001421973,0.00009657524,0.00003130006],"domain_scores_gemma":[0.9981971,0.001340404,0.0001951227,0.0001116956,0.0001304683,0.00002524282],"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":[0.0004511646,0.0002194946,0.0476215,0.0001051665,0.0003070701,0.000500289,0.000260378,0.917509,0.01588191,0.001081399,0.0003012225,0.01576151],"study_design_scores_gemma":[0.00004361578,0.001226381,0.02829355,0.00002512117,0.0001971218,0.0006721718,0.0001821808,0.9560586,0.0102226,0.00148355,0.001536127,0.00005897648],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9454336,0.000317861,0.05202311,0.0001246055,0.000007914377,0.00009314737,0.0004021943,0.00007860098,0.001518981],"genre_scores_gemma":[0.9896337,0.0001834296,0.009368854,0.00003279795,0.000004424271,0.0000681911,0.0002104969,0.00001508875,0.0004829765],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007709357,"threshold_uncertainty_score":0.01532894,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04396567815379671,"score_gpt":0.3414649629697665,"score_spread":0.2974992848159698,"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."}}