{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001307462,0.0002347526,0.0004418378,0.00008967056,0.0001249024,0.00002418742,0.0001099942,0.000142036,0.000005823015],"category_scores_gemma":[0.00005129856,0.0001976771,0.00005820475,0.00004623925,0.0001044517,0.00001766338,0.000135825,0.0002090938,1.083843e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000161079,"about_ca_system_score_gemma":0.00007414676,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005212526,"about_ca_topic_score_gemma":0.0002001258,"domain_scores_codex":[0.9981277,0.0003409441,0.000595376,0.0004153302,0.0001843236,0.0003363389],"domain_scores_gemma":[0.9990852,0.00009734081,0.0002415592,0.0001729445,0.00001471693,0.00038817],"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":[0.0008924116,0.002247909,0.07907455,0.00004205823,0.00006349145,0.0001296305,0.0003871071,0.01272874,0.9005146,5.926303e-7,0.00001696588,0.003901946],"study_design_scores_gemma":[0.05308764,0.1356327,0.3646791,0.0002309365,0.000580137,0.007539924,0.03949837,0.05344715,0.3415354,0.0002691855,0.0009440706,0.002555348],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9929146,0.0005263189,0.005530153,0.0001868523,0.00004915366,0.00074724,0.00003906948,0.00000290341,0.000003677816],"genre_scores_gemma":[0.9930223,0.00008097383,0.005960539,0.0007387684,0.00009654316,0.00004691906,0.00002887282,0.00002165669,0.000003405678],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5589792,"threshold_uncertainty_score":0.806104,"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."}}