{"id":"W4250416470","doi":"10.1515/iupac.78.0473","title":"Pharmacokinetics","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Pharmaceutical studies and practices","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Glossary; Chemical nomenclature; Relation (database); Computer science; Management science; Data science; Chemistry; Engineering; Data mining","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":[0.001710738,0.001740453,0.001896193,0.003219946,0.0006285764,0.003052333,0.002407783,0.002243979,0.1621366],"category_scores_gemma":[0.01783381,0.0006193654,0.002258236,0.00524175,0.000329548,0.001996947,0.001541751,0.002175333,0.1117838],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00224097,"about_ca_system_score_gemma":0.003617367,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01312127,"about_ca_topic_score_gemma":0.02262201,"domain_scores_codex":[0.9984009,0.0003437966,0.0003827907,0.0004337945,0.0003238025,0.0001149735],"domain_scores_gemma":[0.9928471,0.003295907,0.001179642,0.001113956,0.001263703,0.0002997043],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002665737,0.00003316308,0.001796338,0.00511109,0.0001393984,0.00004945278,0.00002382041,0.0004529155,0.0001387968,0.001226278,0.9743457,0.01641642],"study_design_scores_gemma":[0.0004334022,0.00003779003,0.004164761,0.002074746,0.0001523794,0.0001922592,0.00002573536,0.0003674413,0.0001797906,0.003280696,0.9890527,0.00003840413],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001061484,0.0006898667,0.0002006474,0.0001769767,0.00002743374,0.0000390452,0.9966246,0.000274177,0.001861017],"genre_scores_gemma":[0.001161864,0.001104467,0.001026471,0.0005182133,0.00003675044,0.0003497658,0.9938768,0.0001327592,0.00179289],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1621366,"threshold_uncertainty_score":0.5424009,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05066726583638164,"score_gpt":0.5137645949517565,"score_spread":0.4630973291153749,"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."}}