{"id":"W2046095427","doi":"10.1208/s12248-014-9647-y","title":"Making the Most of Clinical Data: Reviewing the Role of Pharmacokinetic-Pharmacodynamic Models of Anti-malarial Drugs","year":2014,"lang":"en","type":"review","venue":"The AAPS Journal","topic":"Malaria Research and Control","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":false,"ca_institutions":"Royal Ottawa Mental Health Centre","funders":"Victorian Centre for Biostatistics; National Health and Medical Research Council; Wellcome Trust","keywords":"Pharmacodynamics; Drug development; Computer science; Population; Bayesian probability; Artificial intelligence; Medicine; Pharmacology; Drug; Pharmacokinetics","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":"codex-gemma-dda1882f352a","candidate_categories":["research_integrity"],"consensus_categories":[],"category_scores_codex":[0.01722085,0.0003799956,0.003290957,0.000136399,0.0002091088,0.00004461044,0.003196161,0.0001854045,0.0002567912],"category_scores_gemma":[0.001356363,0.0001467431,0.001206468,0.0004265125,0.0005520318,0.0001315303,0.0007985519,0.003098848,0.000008164517],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003075866,"about_ca_system_score_gemma":0.001186839,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002789656,"about_ca_topic_score_gemma":8.604081e-7,"domain_scores_codex":[0.9913225,0.003442894,0.003124905,0.0003178514,0.001310392,0.0004814763],"domain_scores_gemma":[0.9918424,0.002377768,0.003293487,0.001829364,0.0004936488,0.0001633149],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003299098,0.0001343546,0.000008386744,0.006113458,0.001935921,0.0000129771,0.0001147191,0.00005677211,0.0001231639,0.00098503,0.001581185,0.9886041],"study_design_scores_gemma":[0.00258549,0.0002122467,0.00001728703,0.0224872,0.01070513,0.0007181997,0.0001196698,0.02959356,0.00001490069,0.0005133475,0.9328372,0.0001958048],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00009566722,0.9939505,0.0006903143,0.00135588,0.0005503898,0.001527127,0.000134738,0.00000638724,0.001688998],"genre_scores_gemma":[0.03361457,0.9632374,0.0001029537,0.0001766154,0.002690374,0.00001574292,0.00002928861,0.00005591066,0.00007712328],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9884083,"threshold_uncertainty_score":0.9992011,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2113417266238842,"score_gpt":0.493273658794199,"score_spread":0.2819319321703149,"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."}}