{"id":"W2112139971","doi":"10.18433/j3np5n","title":"A Correlative Model to Predict In Vivo AUC for Nanosystem Drug Delivery with Release Rate-Limited Absorption","year":2012,"lang":"en","type":"article","venue":"Journal of Pharmacy & Pharmaceutical Sciences","topic":"Drug Solubulity and Delivery Systems","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Drug Applied Research Center, Tabriz University of Medical Sciences; University of Tabriz; Tabriz University of Medical Sciences","keywords":"IVIVC; In vivo; Drug; Drug delivery; Pharmacology; Computer science; Absorption (acoustics); In vitro; Biochemical engineering; Chemistry; Biomedical engineering; Medicine; Materials science; Nanotechnology; Engineering; Biology; Biochemistry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009133336,0.0007123486,0.0006465418,0.0004634632,0.0002004421,0.0005721636,0.0008646576,0.001060546,0.001567552],"category_scores_gemma":[0.001930755,0.0002839651,0.0006569004,0.0002856407,0.0003401131,0.0004266849,0.000315021,0.0007632065,0.0006013993],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007784212,"about_ca_system_score_gemma":0.0007424895,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004035095,"about_ca_topic_score_gemma":0.002405667,"domain_scores_codex":[0.9997177,0.00009031367,0.00001498176,0.00007757392,0.00006919612,0.00003016576],"domain_scores_gemma":[0.9993848,0.0003539705,0.0001062732,0.00003321189,0.000108548,0.00001321927],"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":[0.0001012636,0.00009749453,0.001662447,0.00008832038,0.00004724605,0.00009186011,0.00003652814,0.9731406,0.005031912,0.001190227,0.0004659701,0.01804615],"study_design_scores_gemma":[0.000002942827,0.00003033078,0.0002358932,0.000003465303,0.000007617602,0.00001589155,0.00000159568,0.998791,0.0006651605,0.0001310067,0.0001117939,0.00000316822],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1694169,0.0008762706,0.8229318,0.0003198611,0.00008313055,0.0001953103,0.0002877423,0.001422808,0.004466224],"genre_scores_gemma":[0.9641163,0.0003000466,0.03193452,0.00009198712,0.0000348632,0.0002670014,0.0001693377,0.00006289846,0.003023149],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004035095,"threshold_uncertainty_score":0.008023202,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1625059310219107,"score_gpt":0.4394556950145615,"score_spread":0.2769497639926508,"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."}}