{"id":"W4284898604","doi":"10.3390/pharmaceutics14071426","title":"Model Re-Estimation: An Alternative for Poor Predictive Performance during External Evaluations? Example of Gentamicin in Critically Ill Patients","year":2022,"lang":"en","type":"article","venue":"Pharmaceutics","topic":"Antibiotics Pharmacokinetics and Efficacy","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Centre Hospitalier Universitaire Sainte-Justine; Institut universitaire de cardiologie et de pneumologie de Québec; Hôpital du Sacré-Cœur de Montréal; Université de Montréal","funders":"Fonds de Recherche du Québec - Santé; Réseau Québécois de Recherche sur les Médicaments","keywords":"Dosing; Medicine; NONMEM; Critically ill; Nomogram; Intensive care medicine; Estimation; Population; Covariate; Statistics; Internal medicine","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003789986,0.0001399857,0.0002202583,0.0001749541,0.0001540985,0.000008934438,0.000151623,0.00002593085,0.0001181761],"category_scores_gemma":[0.000145664,0.0001523626,0.00005764694,0.0001707978,0.00006287405,0.0001365923,0.0001158688,0.0002622998,0.00000157619],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002589276,"about_ca_system_score_gemma":0.0001141672,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002017651,"about_ca_topic_score_gemma":0.000001261256,"domain_scores_codex":[0.9984516,0.0000638299,0.0004412045,0.0002708559,0.0005061154,0.000266411],"domain_scores_gemma":[0.9986743,0.00007241989,0.0001295285,0.0001649032,0.0008309421,0.000127862],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00264294,0.002780147,0.06039686,0.0005110095,0.0001095671,0.000008770998,0.003652547,0.8774232,0.04176237,0.0003290249,0.0001638488,0.0102197],"study_design_scores_gemma":[0.005536758,0.0005959015,0.02852345,0.00005124086,0.0001727377,0.000005452826,0.0001813809,0.9195488,0.04493655,0.0001883596,0.0001308714,0.0001284914],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9731288,0.00006709879,0.02486116,0.0003094205,0.000182436,0.001028221,0.0002026499,0.000022763,0.0001974551],"genre_scores_gemma":[0.988083,0.00007739049,0.01036586,0.001111983,0.00007439404,0.00005734344,0.0001129441,0.00003207879,0.00008498646],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04212559,"threshold_uncertainty_score":0.6213165,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1067039997195367,"score_gpt":0.4085653606468886,"score_spread":0.3018613609273519,"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."}}