{"id":"W2061459550","doi":"10.1007/s40262-013-0065-6","title":"The Integration of Allometry and Virtual Populations to Predict Clearance and Clearance Variability in Pediatric Populations over the Age of 6 Years","year":2013,"lang":"en","type":"article","venue":"Clinical Pharmacokinetics","topic":"Pharmacogenetics and Drug Metabolism","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":46,"is_retracted":false,"has_abstract":false,"ca_institutions":"Blackberry (Canada); University of Waterloo","funders":"","keywords":"Allometry; Biology; Pharmacotherapy; Medicine; Demography; Ecology; Internal medicine","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":[0.005549954,0.0007215075,0.001293608,0.001679641,0.0003397656,0.001876184,0.0008648958,0.0008516533,0.0009999893],"category_scores_gemma":[0.02214505,0.0003350389,0.001068227,0.001180913,0.0003955324,0.001694765,0.00109518,0.001163275,0.0004980782],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005397098,"about_ca_system_score_gemma":0.000800286,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003046022,"about_ca_topic_score_gemma":0.001987921,"domain_scores_codex":[0.9976375,0.001279712,0.0001190926,0.0005378076,0.0003115734,0.0001143333],"domain_scores_gemma":[0.9899936,0.005517458,0.001934615,0.001319316,0.0008657572,0.000369136],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00124912,0.0001904967,0.9031802,0.00004864797,0.0007727774,0.0001819614,0.0002656964,0.02458902,0.00132237,0.0009888144,0.001237328,0.06597353],"study_design_scores_gemma":[0.00009121789,0.001753373,0.430524,0.00005208267,0.0005801783,0.002242329,0.0003877561,0.5521409,0.002604425,0.006912992,0.002619442,0.00009142518],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9585674,0.0008706052,0.03715361,0.0002310677,0.00007044304,0.00006208962,0.001159091,0.0005685926,0.001317186],"genre_scores_gemma":[0.9928349,0.0001558142,0.005958506,0.00005858267,0.00002653371,0.00003462736,0.0006691656,0.00007068334,0.0001912553],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005549954,"threshold_uncertainty_score":0.02935129,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1606576739703237,"score_gpt":0.4787806706320287,"score_spread":0.318122996661705,"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."}}