{"id":"W2781982724","doi":"10.1039/c7nr09237g","title":"Se@SiO<sub>2</sub>–FA–CuS nanocomposites for targeted delivery of DOX and nano selenium in synergistic combination of chemo-photothermal therapy","year":2018,"lang":"en","type":"article","venue":"Nanoscale","topic":"Nanoplatforms for cancer theranostics","field":"Engineering","cited_by":102,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Cancer Research","funders":"Shanghai University of Engineering and Science; Science and Technology Commission of Shanghai Municipality; Shanghai Municipal Education Commission; National Natural Science Foundation of China","keywords":"Photothermal therapy; Selenium; Drug delivery; Nanocomposite; Materials science; Nanotechnology; Nano-; Cancer therapy; Photothermal effect; Delivery system; Nanoparticle; Chemotherapy; Cancer; Pharmacology; Medicine; Metallurgy","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":[0.000143019,0.0002097805,0.0003647759,0.0001827536,0.00004591855,0.00001129694,0.0001505467,0.000182036,0.00001382752],"category_scores_gemma":[0.00002216217,0.0002081703,0.00006758558,0.0003222192,0.0001510075,0.0001468167,0.0000239759,0.00008771011,0.000002493768],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008149338,"about_ca_system_score_gemma":0.00003591329,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003926899,"about_ca_topic_score_gemma":0.00005592916,"domain_scores_codex":[0.9988881,0.0000152661,0.0004380853,0.0002001074,0.0001762545,0.0002821947],"domain_scores_gemma":[0.999293,0.000140816,0.0001144043,0.0002146045,0.0001842798,0.00005284847],"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":[0.0002398274,0.00008922449,0.0008836724,0.0002049455,0.00005202856,5.687746e-7,0.0005322341,0.0001263264,0.9935556,0.00005706739,0.0001724829,0.004085994],"study_design_scores_gemma":[0.002394279,0.0004016434,0.002751262,0.0001189013,0.00002062411,0.000002174138,0.00002889581,0.003351392,0.9900057,0.000260899,0.0004482168,0.0002160492],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9969875,0.001067782,0.0006959831,0.000008533429,0.0003372155,0.0005752918,0.00009416699,0.00007709896,0.0001563895],"genre_scores_gemma":[0.9986481,0.000333521,0.0007711425,0.00002322294,0.00005737676,0.00005111149,0.00003130739,0.00006348365,0.00002073209],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003869945,"threshold_uncertainty_score":0.8488939,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008300389319868394,"score_gpt":0.2107478402945203,"score_spread":0.2024474509746519,"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."}}