{"id":"W4386939740","doi":"10.2139/ssrn.4570987","title":"Does Sample Size, Sampling Strategy, or Handling of Concentrations Below the Lower Limit of Quantification Matter When Externally Evaluating Population Pharmacokinetic Models?","year":2023,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Antibiotics Pharmacokinetics and Efficacy","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Sampling (signal processing); Limit (mathematics); Sample size determination; Statistics; Sample (material); Population; Econometrics; Mathematics; Environmental science; Computer science; Chromatography; Chemistry; Medicine; Environmental health; Mathematical analysis","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":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.2417496,0.001313536,0.002624826,0.001072632,0.0008354181,0.004156301,0.002395235,0.002946168,0.002652825],"category_scores_gemma":[0.560805,0.0008802044,0.001940395,0.001226873,0.003189619,0.003635519,0.001854211,0.002563323,0.00119247],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009366781,"about_ca_system_score_gemma":0.00292202,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002095682,"about_ca_topic_score_gemma":0.002821153,"domain_scores_codex":[0.8598915,0.116327,0.00755519,0.004520622,0.01091539,0.0007903146],"domain_scores_gemma":[0.5394437,0.3999192,0.02014577,0.02372084,0.01562776,0.001142776],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.007960751,0.001042063,0.2191193,0.006713032,0.009479206,0.0009432399,0.00327241,0.03364243,0.03509702,0.03008589,0.02754394,0.6251008],"study_design_scores_gemma":[0.003297597,0.01113478,0.2620033,0.007196563,0.01173384,0.00494813,0.002032155,0.2784768,0.1094705,0.2052085,0.1034048,0.001093028],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1281801,0.005467529,0.8356812,0.01512543,0.00253373,0.002160481,0.001492175,0.001787738,0.007571466],"genre_scores_gemma":[0.5896123,0.002239365,0.3919308,0.009109843,0.001284927,0.002214764,0.001029688,0.001174526,0.001403781],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7582504,"threshold_uncertainty_score":0.9350578,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1039919436683307,"score_gpt":0.3837478811609636,"score_spread":0.2797559374926329,"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."}}