{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005960444,0.0005495198,0.0006082742,0.0004447756,0.0001898966,0.0005124474,0.0002821306,0.0005778468,0.0008887249],"category_scores_gemma":[0.0008330652,0.0002701926,0.0004717813,0.0002915913,0.0003377622,0.0003840417,0.0004840308,0.0003763237,0.0002033308],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006342654,"about_ca_system_score_gemma":0.0005554294,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000533284,"about_ca_topic_score_gemma":0.0008409246,"domain_scores_codex":[0.9997603,0.00006656448,0.00001091668,0.00003891643,0.00009956516,0.00002374724],"domain_scores_gemma":[0.9998149,0.00009975785,0.00003765857,0.000009751234,0.00003004784,0.000007835845],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00005660067,0.0000852477,0.000364186,0.0002230306,0.00003426031,0.00007743363,0.00003650579,0.8671363,0.09300583,0.01258513,0.0005340103,0.02586155],"study_design_scores_gemma":[0.00001017225,0.00009660406,0.0001962463,0.00001138043,0.00001313829,0.00003060119,0.000009060742,0.9806793,0.01432811,0.002315018,0.002302499,0.000007926636],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08079743,0.001684013,0.9085059,0.0002413358,0.00005327938,0.0000904874,0.0000646646,0.0001663475,0.008396542],"genre_scores_gemma":[0.6653659,0.001646513,0.3264724,0.0001232601,0.0000284484,0.0002846511,0.0001250878,0.0001164289,0.005837294],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0008887249,"threshold_uncertainty_score":0.004601955,"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."}}