{"id":"W2612381369","doi":"10.1021/acs.molpharmaceut.6b01015","title":"Leveraging Colloidal Aggregation for Drug-Rich Nanoparticle Formulations","year":2017,"lang":"en","type":"article","venue":"Molecular Pharmaceutics","topic":"Nanoparticle-Based Drug Delivery","field":"Materials Science","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Cancer Institute; National Institute of General Medical Sciences; Natural Sciences and Engineering Research Council of Canada; Canadian Cancer Society Research Institute","keywords":"Ethylene glycol; Nanoparticle; Polymer; Drug; Chemistry; Colloid; Drug delivery; PEG ratio; Chemical engineering; Amphiphile; Polyvinyl alcohol; Nanotechnology; Chromatography; Materials science; Organic chemistry; Pharmacology; Copolymer","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":[0.0005651464,0.0001756854,0.0001705401,0.00006083234,0.001014734,0.0004107078,0.0004685458,0.00004889608,0.00007967967],"category_scores_gemma":[0.000242157,0.0001898479,0.00008960137,0.0000876084,0.0001178135,0.00047912,0.0001526142,0.0000874926,0.00016782],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000107251,"about_ca_system_score_gemma":0.00009940341,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000221828,"about_ca_topic_score_gemma":0.000007801415,"domain_scores_codex":[0.9984515,0.00006732026,0.000306162,0.0003494813,0.0003278825,0.0004976208],"domain_scores_gemma":[0.9986561,0.0000923144,0.0002277973,0.000643654,0.0002174523,0.0001626905],"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":[0.00005203358,0.00008699809,0.001071829,0.00002823308,0.00001327348,0.00001537125,0.0002754555,0.003002527,0.9920241,0.0008654107,0.0003764168,0.002188373],"study_design_scores_gemma":[0.001587608,0.00002504709,0.0002242519,0.00001835913,0.00008634885,0.000005353364,0.00003855539,0.04196483,0.9507491,0.001144805,0.003922181,0.0002335365],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9772521,0.000164937,0.01959567,0.001279231,0.0006219248,0.0006389049,0.0000354484,0.0001252711,0.0002865278],"genre_scores_gemma":[0.9931637,0.000006319587,0.005717172,0.000567024,0.00009636809,0.000104235,0.00001094071,0.00003924881,0.0002949663],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04127495,"threshold_uncertainty_score":0.7804614,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04239746323312041,"score_gpt":0.3304566997136694,"score_spread":0.288059236480549,"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."}}