{"id":"W1970977102","doi":"10.1002/jps.23502","title":"Toward a new paradigm for the efficient in vitro–in vivo extrapolation of metabolic clearance in humans from hepatocyte data","year":2013,"lang":"en","type":"article","venue":"Journal of Pharmaceutical Sciences","topic":"Pharmacogenetics and Drug Metabolism","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":52,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"In vivo; Hepatocyte; In vitro; Extrapolation; Metabolic clearance rate; Chemistry; Cell biology; Biology; Computational biology; Pharmacology; Biochemistry; Pharmacokinetics; Genetics; 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":[0.03115271,0.001292201,0.002837192,0.001849699,0.0007722173,0.00648547,0.002744141,0.001710319,0.002137066],"category_scores_gemma":[0.0291888,0.001132792,0.001163887,0.001203657,0.002086819,0.004154119,0.002582941,0.007714272,0.002022721],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001206501,"about_ca_system_score_gemma":0.002631877,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001563693,"about_ca_topic_score_gemma":0.001552897,"domain_scores_codex":[0.983252,0.01191498,0.0008921705,0.001583423,0.002161958,0.0001953052],"domain_scores_gemma":[0.9802367,0.008220953,0.001468059,0.006543922,0.003091944,0.0004384844],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003726847,0.001634964,0.02161712,0.001953444,0.001263065,0.0008127419,0.001404855,0.01444572,0.5191932,0.0966413,0.01373097,0.3235758],"study_design_scores_gemma":[0.0005663376,0.008489064,0.0201764,0.0008839099,0.001423297,0.008696239,0.001090485,0.118996,0.5304702,0.1476991,0.1610431,0.0004658973],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01970116,0.005042031,0.9658726,0.003894064,0.0004117404,0.0002596841,0.0007467112,0.0007478565,0.003324123],"genre_scores_gemma":[0.3309032,0.009009538,0.6462247,0.005630169,0.0009391342,0.001188949,0.002122727,0.001214355,0.002767253],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03115271,"threshold_uncertainty_score":0.1647533,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3159447964285114,"score_gpt":0.4846943504884899,"score_spread":0.1687495540599785,"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."}}