{"id":"W2809560445","doi":"10.1016/j.actbio.2018.05.031","title":"Engineering folate-targeting diselenide-containing triblock copolymer as a redox-responsive shell-sheddable micelle for antitumor therapy in vivo","year":2018,"lang":"en","type":"article","venue":"Acta Biomaterialia","topic":"Advanced Polymer Synthesis and Characterization","field":"Chemistry","cited_by":72,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"Iran Science Elites Federation; Iran's National Elites Foundation; Universität Zürich; Royan Institute; Iran National Science Foundation; National Science Foundation","keywords":"Diselenide; In vivo; Materials science; Micelle; Copolymer; Redox; Nanotechnology; Chemistry; Aqueous solution; Organic chemistry; Selenium; Composite material; Polymer; 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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001782393,0.0003184772,0.0003881787,0.0001289946,0.0001656204,0.0001351717,0.0002541428,0.0001702241,0.002100222],"category_scores_gemma":[0.0001443222,0.0003112427,0.0000947933,0.0001859961,0.00005348376,0.0003036303,0.0000618972,0.00005422142,0.0000324698],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007095567,"about_ca_system_score_gemma":0.00005666523,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001571059,"about_ca_topic_score_gemma":0.000005342073,"domain_scores_codex":[0.9982995,0.00002466682,0.0005172162,0.0004697207,0.0001395526,0.000549329],"domain_scores_gemma":[0.9991655,0.0001168783,0.0002353504,0.0003113596,0.00007822947,0.00009263089],"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":[0.001237938,0.00005866924,0.0003400436,0.00006575142,0.0000479499,0.000007857881,0.0006064241,0.00000110324,0.9967129,0.00004521737,0.0003772032,0.000498968],"study_design_scores_gemma":[0.001282278,0.0001441024,0.00007258501,0.0001547232,0.00001772125,0.000006971474,0.0002127252,0.0005583342,0.9734816,0.00003963734,0.02364762,0.0003817098],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.997684,0.0002363149,0.0002039887,0.00009264821,0.0009456846,0.0002221146,0.0001210834,0.0001511246,0.0003430686],"genre_scores_gemma":[0.9968352,0.00007828391,0.000673051,0.0000782654,0.0007476484,0.0001195547,0.00009732279,0.00009144206,0.001279225],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02327042,"threshold_uncertainty_score":0.999934,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009052854550171227,"score_gpt":0.244558685464642,"score_spread":0.2355058309144708,"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."}}