{"id":"W2430048569","doi":"10.3390/nano6060116","title":"Human Serum Albumin Nanoparticles for Use in Cancer Drug Delivery: Process Optimization and In Vitro Characterization","year":2016,"lang":"en","type":"article","venue":"Nanomaterials","topic":"Nanoparticle-Based Drug Delivery","field":"Materials Science","cited_by":187,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Victoria Hospital; Université de Montréal","funders":"","keywords":"Drug delivery; Drug; Cancer; In vitro; Nanoparticle; Human serum albumin; Albumin; Characterization (materials science); Process (computing); Chemistry; Pharmacology; Nanotechnology; Materials science; Medicine; Biochemistry; Computer science; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0007400016,0.0005017613,0.0004418032,0.0003356556,0.0001995764,0.0003718848,0.0002496428,0.0004193388,0.0005272964],"category_scores_gemma":[0.000458545,0.0001859495,0.00044816,0.0004889943,0.0001868039,0.0002909387,0.0002229157,0.0004065115,0.00036755],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004229094,"about_ca_system_score_gemma":0.0003226687,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009917355,"about_ca_topic_score_gemma":0.001425954,"domain_scores_codex":[0.9995754,0.00007247306,0.0000512238,0.0000756307,0.0001851293,0.00004007736],"domain_scores_gemma":[0.9998463,0.00003314944,0.00003873581,0.00001036732,0.00006295242,0.000008494955],"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":[0.00005713884,0.00006142235,0.0001220111,0.0001941053,0.000008959985,0.00006167332,0.0000405997,0.0005912579,0.9927914,0.0000964889,0.00008261859,0.005892298],"study_design_scores_gemma":[0.000006149901,0.0002013526,0.0006347241,0.000007521734,0.00001651194,0.00008733927,0.00001201302,0.001420153,0.9940937,0.00004072125,0.003471993,0.000007839759],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8542807,0.01860625,0.1174352,0.0006253583,0.0001642843,0.000840925,0.001317206,0.0005425047,0.006187653],"genre_scores_gemma":[0.8948969,0.01319249,0.08156633,0.0002624312,0.00005951794,0.0009487091,0.001625166,0.0001637145,0.007284641],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009917355,"threshold_uncertainty_score":0.003913581,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0199838046915035,"score_gpt":0.2657087234089422,"score_spread":0.2457249187174388,"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."}}