{"id":"W1982471127","doi":"10.1016/s0009-9236(03)90668-0","title":"Population Pharmacokinetics of Meropenem in Febrile Neutropenics Using NPEM and Optimal Sampling Design","year":2003,"lang":"en","type":"article","venue":"Clinical Pharmacology & Therapeutics","topic":"Antibiotics Pharmacokinetics and Efficacy","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Meropenem; Pharmacokinetics; Medicine; Population pharmacokinetics; Clinical pharmacology; Pharmacology; Sampling (signal processing); Population; Intensive care medicine; Antibiotics; Biology; Computer science; Microbiology; Environmental health; Antibiotic resistance","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":[0.01831735,0.0009455636,0.002482882,0.0006075601,0.0002574155,0.001100695,0.0009475974,0.0009603145,0.0008749628],"category_scores_gemma":[0.03407552,0.001212513,0.001070184,0.0004653721,0.0009606301,0.001236366,0.001102614,0.001624506,0.0001242323],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008819599,"about_ca_system_score_gemma":0.00185825,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001464365,"about_ca_topic_score_gemma":0.0009324942,"domain_scores_codex":[0.9853981,0.01278022,0.0002700782,0.0007256983,0.0005844459,0.0002415062],"domain_scores_gemma":[0.9805256,0.01565447,0.001613361,0.001168934,0.000725565,0.0003121504],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.09375062,0.004224087,0.08239964,0.0007102327,0.002228452,0.0003719283,0.001293922,0.5645989,0.01048908,0.00935119,0.001370252,0.2292118],"study_design_scores_gemma":[0.003123756,0.0183553,0.02301892,0.00004917226,0.0007348762,0.0002940286,0.0001185588,0.9391878,0.00536863,0.008290374,0.001348588,0.0001099679],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6752859,0.0004489306,0.3214925,0.0002103835,0.00004199347,0.001436815,0.0002268295,0.000255043,0.0006016007],"genre_scores_gemma":[0.9145984,0.0002597355,0.08281664,0.0001386612,0.00003898945,0.001431825,0.0002747611,0.00003910574,0.0004019149],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01831735,"threshold_uncertainty_score":0.09687251,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2362316924799184,"score_gpt":0.4720359587662643,"score_spread":0.2358042662863459,"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."}}