{"id":"W2735494612","doi":"10.1115/1.4038202","title":"Nanoparticle Optimization for Enhanced Targeted Anticancer Drug Delivery","year":2017,"lang":"en","type":"article","venue":"Journal of Biomechanical Engineering","topic":"Nanoparticle-Based Drug Delivery","field":"Materials Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Drug delivery; Drug; Targeted drug delivery; Cancer drugs; Nanoparticle; Nanotechnology; Computer science; Medicine; Pharmacology; Materials science","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.000797692,0.0001389693,0.000291895,0.0001008412,0.000177341,0.0001802754,0.0004561804,0.00006090001,0.00008959944],"category_scores_gemma":[0.0005779387,0.0001237444,0.0001360027,0.00008496646,0.00003836044,0.0006748114,0.00007600115,0.00009884519,0.0000161044],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001008122,"about_ca_system_score_gemma":0.00007836123,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000775755,"about_ca_topic_score_gemma":0.000001404245,"domain_scores_codex":[0.9986121,0.00002070953,0.0005232138,0.0001724333,0.0002988729,0.0003726507],"domain_scores_gemma":[0.9986386,0.0001286747,0.0004321471,0.0003109646,0.0002955393,0.0001940603],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001310233,0.00005850978,0.000006540445,0.00002803716,0.00001557952,0.000008976964,0.00003138011,0.05862572,0.9398685,0.0001701438,0.00007094553,0.0009846824],"study_design_scores_gemma":[0.0008604149,0.0001186037,0.00002429627,0.00006726946,0.00003186083,0.000007961616,0.00001129006,0.2206894,0.7778928,0.00006216218,0.0001113265,0.0001225932],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7720378,0.0001287039,0.2262888,0.0002891042,0.001090105,0.0001167528,0.0000098437,0.00003371776,0.000005191294],"genre_scores_gemma":[0.9591951,0.00002600695,0.04040337,0.0000465119,0.0002789463,0.000008458117,7.736991e-7,0.00002601945,0.00001481724],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1871573,"threshold_uncertainty_score":0.5046149,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01083354362055706,"score_gpt":0.2396984253017722,"score_spread":0.2288648816812152,"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."}}