{"id":"W2974456218","doi":"10.3390/app9183899","title":"Polymers and Polymer Nanocomposites for Cancer Therapy","year":2019,"lang":"en","type":"article","venue":"Applied Sciences","topic":"Hydrogels: synthesis, properties, applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":93,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Polymer; Materials science; Fibroin; Nanocomposite; Polymer science; Self-healing hydrogels; Biopolymer; Polyester; Chitosan; Drug delivery; Nanotechnology; Drug carrier; Chemical engineering; Chemistry; Polymer chemistry; Organic chemistry; SILK; Composite material","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001255098,0.00009326652,0.00008727593,0.00002796803,0.0001694442,0.0000366567,0.0002078287,0.00005351279,0.00005928613],"category_scores_gemma":[0.000003090422,0.00007169817,0.0000293265,0.00008475181,0.0002433671,0.000003357775,0.00004323043,0.00002038182,0.00001012824],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003944496,"about_ca_system_score_gemma":0.00006077033,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005128381,"about_ca_topic_score_gemma":0.00001346128,"domain_scores_codex":[0.9992741,0.000007971986,0.00009005314,0.0003506017,0.00008657099,0.0001907297],"domain_scores_gemma":[0.9997225,0.00001652438,0.00004179559,0.0001628038,0.0000135404,0.0000427779],"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":[0.00002090596,0.0000127916,0.001460911,0.00000348219,0.0000141212,8.272962e-9,0.00004448002,0.000006197827,0.9740163,0.00101093,0.00008823967,0.02332163],"study_design_scores_gemma":[0.0001945114,0.00007040433,0.0005161431,0.000002494896,0.000004084049,8.967302e-7,0.0000856349,0.00003657285,0.9410856,0.00007090837,0.05781337,0.0001194251],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9850386,0.005131756,0.00007838445,0.0004378384,0.00004607388,0.0004301492,0.0000112391,0.00001185071,0.008814139],"genre_scores_gemma":[0.9968504,0.0003042767,0.0004886913,0.0006851038,0.00006678262,0.0003140919,0.000005953682,0.00001035768,0.001274383],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05772513,"threshold_uncertainty_score":0.2923767,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01715427814961967,"score_gpt":0.2622716614367947,"score_spread":0.245117383287175,"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."}}