{"id":"W2072139355","doi":"10.1016/j.biomaterials.2012.02.019","title":"Tumor-targeted drug delivery using MR-contrasted docetaxel – Carboxymethylcellulose nanoparticles","year":2012,"lang":"en","type":"article","venue":"Biomaterials","topic":"Nanoparticle-Based Drug Delivery","field":"Materials Science","cited_by":58,"is_retracted":false,"has_abstract":false,"ca_institutions":"Princess Margaret Cancer Centre; Ontario Institute for Cancer Research","funders":"Center for Information Technology; Canadian Institutes of Health Research; Ontario Institute for Cancer Research; Cancer Research Institute","keywords":"Docetaxel; Biodistribution; Nanoparticle; Pharmacokinetics; Materials science; Magnetic resonance imaging; Drug delivery; Pharmacology; Cancer research; Medicine; Chemotherapy; Chemistry; Nanotechnology; Internal medicine; Radiology; In vitro","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002093968,0.000507129,0.0007036252,0.0002153148,0.0003283514,0.0003211756,0.0005089422,0.0001298645,0.001735258],"category_scores_gemma":[0.0001818137,0.0004613569,0.0001927565,0.0004362325,0.0002716243,0.001172301,0.0002678649,0.00003013848,0.001915292],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002258618,"about_ca_system_score_gemma":0.0001707687,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009477476,"about_ca_topic_score_gemma":0.00001795892,"domain_scores_codex":[0.9952887,0.0007514736,0.001025329,0.0006123633,0.0006054206,0.00171671],"domain_scores_gemma":[0.997839,0.0001999715,0.0004426803,0.0007561138,0.0001844716,0.0005777189],"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":[0.0002135201,0.0003171213,0.001555872,0.00006249433,0.00003606305,0.00004010027,0.000413659,0.00002226623,0.9966978,0.00008946285,0.0004290008,0.0001226238],"study_design_scores_gemma":[0.00106684,0.00004410643,0.001525724,0.00005973675,0.0001506532,0.00005037291,0.0001858306,0.0002085733,0.9954914,0.00007146734,0.0005319338,0.0006133568],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.99252,0.002295875,0.00002576146,0.00007591589,0.003680769,0.0005863528,0.0002127109,0.0005464066,0.00005616681],"genre_scores_gemma":[0.9954168,0.00000959975,0.003307247,0.0002918181,0.000756893,0.00005241071,0.0000219224,0.00009126104,0.00005205658],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003281486,"threshold_uncertainty_score":0.9997838,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0223099380918587,"score_gpt":0.2470208536840894,"score_spread":0.2247109155922307,"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."}}