{"id":"W2759724202","doi":"10.1021/acs.molpharmaceut.7b00670","title":"Using Flash Nanoprecipitation To Produce Highly Potent and Stable Cellax Nanoparticles from Amphiphilic Polymers Derived from Carboxymethyl Cellulose, Polyethylene Glycol, and Cabazitaxel","year":2017,"lang":"en","type":"article","venue":"Molecular Pharmaceutics","topic":"Nanoparticle-Based Drug Delivery","field":"Materials Science","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; Ontario Institute for Cancer Research","funders":"Ontario Institute for Cancer Research","keywords":"Nanoparticle; Amphiphile; Polyethylene glycol; Carboxymethyl cellulose; Polymer; Nanomedicine; Chemistry; PEG ratio; Drug carrier; Methacrylate; Cabazitaxel; Copolymer; Solvent; Drug delivery; Materials science; Nanotechnology; Organic chemistry; Sodium; Cancer","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":[0.0001739585,0.0004818975,0.0002093778,0.0002000211,0.0001032114,0.0001998796,0.0002104448,0.0002619779,0.0006007138],"category_scores_gemma":[0.0001471781,0.0001382168,0.0002097185,0.0001126045,0.0002258455,0.0002801511,0.0001994032,0.0003127333,0.0003199165],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003779159,"about_ca_system_score_gemma":0.0001717079,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003952011,"about_ca_topic_score_gemma":0.0008038814,"domain_scores_codex":[0.9998835,0.000009929289,0.000008510062,0.00003419476,0.00004564425,0.00001825175],"domain_scores_gemma":[0.9998837,0.00004040719,0.00003547429,0.00001284451,0.00001443162,0.00001309197],"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":[0.00001079771,0.000006448002,0.00003256124,0.00003521982,0.000003034325,0.0000356444,0.000008184798,0.0001275678,0.9978947,0.00008481646,0.00003048958,0.001730496],"study_design_scores_gemma":[0.000002325766,0.00003373236,0.0001184835,0.000001179626,0.000002931569,0.00005225412,0.000001709261,0.0005569921,0.9984081,0.0000169885,0.0008030667,0.000002111774],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8843624,0.004313604,0.1046393,0.0002223903,0.00009018477,0.0002039228,0.0004463868,0.0006033019,0.005118513],"genre_scores_gemma":[0.9325077,0.002123782,0.05985978,0.0001591631,0.00002735761,0.0001744386,0.0004879508,0.0001103155,0.004549557],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006007138,"threshold_uncertainty_score":0.002742052,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0377968996205972,"score_gpt":0.2958696100860586,"score_spread":0.2580727104654614,"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."}}