{"id":"W2808684989","doi":"10.1016/j.ijbiomac.2018.06.072","title":"Dual-responsive IPN hydrogel based on sugarcane bagasse cellulose as drug carrier","year":2018,"lang":"en","type":"article","venue":"International Journal of Biological Macromolecules","topic":"Hydrogels: synthesis, properties, applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":59,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of New Brunswick","funders":"Guangxi Key Laboratory of Petrochemical Resource Processing and Process Intensification Technology, Guangxi University; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Self-healing hydrogels; Swelling; Thermogravimetric analysis; Drug delivery; Epichlorohydrin; Polymer chemistry; Cellulose; Chemical engineering; Drug carrier; Bagasse; Interpenetrating polymer network; Materials science; Chemistry; Polymerization; Polymer; Nuclear chemistry; Organic chemistry; Composite material","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":[0.0004665699,0.0002551257,0.0002546879,0.0001646807,0.0000900157,0.00006185113,0.0007540133,0.000198677,0.0003523518],"category_scores_gemma":[0.001041234,0.0001878939,0.0002775253,0.0001009554,0.0004461933,0.00000899878,0.0001736544,0.0002156232,0.0001318989],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006943052,"about_ca_system_score_gemma":0.000212965,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003554486,"about_ca_topic_score_gemma":0.00001317406,"domain_scores_codex":[0.9980907,0.000215857,0.0005517603,0.0003886347,0.0004686946,0.0002843676],"domain_scores_gemma":[0.9981517,0.0001110486,0.0003784769,0.0003142033,0.0008373745,0.0002072283],"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":[0.001422079,0.0003342834,0.000748538,0.000002624554,0.000218331,0.0001984621,0.0000571147,0.00006999465,0.9905886,0.0007988226,0.00220884,0.003352308],"study_design_scores_gemma":[0.0007536862,0.001265612,0.001022451,0.00004642791,0.00002462933,0.0003068347,0.00007074358,0.0002474465,0.9374112,0.0009462297,0.05764104,0.0002636526],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9922514,0.0002889296,0.001346296,0.002969614,0.0003891228,0.0001512757,0.0000942624,0.00001529422,0.002493798],"genre_scores_gemma":[0.9946501,0.00009532782,0.0011907,0.002535381,0.0009745275,0.00001929733,0.0000613325,0.00002731865,0.0004460538],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0554322,"threshold_uncertainty_score":0.7662089,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0156270845460587,"score_gpt":0.2733475174540997,"score_spread":0.257720432908041,"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."}}