{"id":"W2901880308","doi":"10.1016/j.msec.2018.11.032","title":"Engineering synthetic artificial pancreas using chitosan hydrogels integrated with glucose-responsive microspheres for insulin delivery","year":2018,"lang":"en","type":"article","venue":"Materials Science and Engineering C","topic":"Pancreatic function and diabetes","field":"Medicine","cited_by":45,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Saskatchewan","funders":"Fundamental Research Funds for the Central Universities; National Natural Science Foundation of China","keywords":"Insulin; Scaffold; Artificial pancreas; Materials science; Self-healing hydrogels; Chitosan; Biomedical engineering; Insulin delivery; Microsphere; Diabetes mellitus; Internal medicine; Chemical engineering; Medicine; Chemistry; Type 1 diabetes; Biochemistry; Endocrinology; Polymer chemistry","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":[0.000339605,0.000179374,0.000289057,0.0001639214,0.0001517555,0.0001331226,0.00007769943,0.00005541165,0.00004718524],"category_scores_gemma":[0.0005747024,0.0001388467,0.0000216436,0.0003736565,0.000231713,0.0001577827,0.00003097145,0.00004838511,0.000007803222],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004979001,"about_ca_system_score_gemma":0.0001741469,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005809712,"about_ca_topic_score_gemma":8.423414e-7,"domain_scores_codex":[0.9989247,0.000007602218,0.0002037422,0.0003020942,0.000191771,0.000370047],"domain_scores_gemma":[0.9993891,0.00007281892,0.00004218142,0.0001704223,0.0001674192,0.0001581243],"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":[0.0002737449,0.00001713731,0.00006650537,0.00007896897,0.00001947336,0.000004061835,0.0001116331,0.0003405814,0.9984817,0.0001013054,0.000007828243,0.0004970501],"study_design_scores_gemma":[0.0004365427,0.0002941988,0.001077016,0.0003038842,0.00006296732,0.00006811989,0.00008344318,0.02747088,0.9695921,0.000005930516,0.000430735,0.0001741811],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9958602,0.0001101469,0.003125283,0.00003883473,0.0004119204,0.0002876354,0.00002144295,0.0001165435,0.00002801013],"genre_scores_gemma":[0.9862217,0.000008971397,0.01337937,0.00007016884,0.0002556114,0.00002278117,0.000005295047,0.00002508009,0.00001102447],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02888961,"threshold_uncertainty_score":0.5662006,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01263471875938194,"score_gpt":0.2246413814704963,"score_spread":0.2120066627111143,"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."}}