{"id":"W4387062717","doi":"10.1016/j.chemosphere.2023.140305","title":"Determination of blood:air, urine:air and plasma:air partition coefficients of selected microbial volatile organic compounds","year":2023,"lang":"en","type":"article","venue":"Chemosphere","topic":"Advanced Chemical Sensor Technologies","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institut de recherche Robert-Sauvé en santé et en sécurité du travail; Université de Montréal","funders":"Institut de Recherche Robert-Sauvé en Santé et en Sécurité du Travail","keywords":"Chemistry; Urine; Partition coefficient; Chromatography; Environmental chemistry; Physiologically based pharmacokinetic modelling; Toxicokinetics; Volatile organic compound; Gas chromatography–mass spectrometry; Room air distribution; Gas chromatography; Mass spectrometry; Pharmacokinetics; Organic chemistry; Toxicity; Pharmacology; Biochemistry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00001869525,0.0001340244,0.0002084706,0.00002617888,0.00002533671,0.000002904308,0.0001132391,0.0001400876,0.00003028682],"category_scores_gemma":[0.000094713,0.0001462163,0.00002821642,0.0006050763,0.00009680224,0.00006616092,0.00005612916,0.0001152238,0.000008511378],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003559666,"about_ca_system_score_gemma":0.000005419449,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000266197,"about_ca_topic_score_gemma":0.00000735201,"domain_scores_codex":[0.9992977,0.000004934353,0.0002445568,0.0001583541,0.0001052546,0.0001892223],"domain_scores_gemma":[0.9995864,0.00005784872,0.00006862484,0.0001672998,0.00008850695,0.00003130067],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000009817547,0.00003699624,0.001273349,0.000281419,0.00001911265,0.0000021775,0.00006259698,0.001961279,0.9943679,0.000004195716,0.000436911,0.001544248],"study_design_scores_gemma":[0.0004946254,0.00003419455,0.002180997,0.00005289879,0.00002955669,0.00000560573,0.00005952241,0.01913521,0.9775454,0.0001240668,0.0002077862,0.0001301022],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.998302,0.00006515601,0.000492397,0.00002054183,0.00006217206,0.0001176401,0.0000226741,0.0007507015,0.0001666825],"genre_scores_gemma":[0.99823,0.00004137198,0.001540895,0.000003439857,0.00001457047,0.000006337359,0.00005384555,0.00003171838,0.00007777683],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01717393,"threshold_uncertainty_score":0.5962527,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005330412368888112,"score_gpt":0.1941431333826759,"score_spread":0.1888127210137878,"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."}}