{"id":"W2959908112","doi":"10.1016/j.msec.2019.109973","title":"Polysaccharide-based tissue-engineered vascular patches","year":2019,"lang":"en","type":"article","venue":"Materials Science and Engineering C","topic":"Electrospun Nanofibers in Biomedical Applications","field":"Materials Science","cited_by":18,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval","funders":"Conselho Nacional de Desenvolvimento Científico e Tecnológico; Natural Sciences and Engineering Research Council of Canada; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Fundação de Amparo à Pesquisa do Estado de São Paulo","keywords":"Biomedical engineering; Pectin; Materials science; Tissue engineering; Vascular tissue; Biocompatible material; Polysaccharide; Polymer; Thrombogenicity; Vascular smooth muscle; Chemistry; Smooth muscle; Composite material; Surgery; Medicine; Biochemistry; Thrombosis","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001035149,0.0002624124,0.0001006343,0.0001056327,0.00005313509,0.0001846296,0.000152228,0.0002564403,0.0006191272],"category_scores_gemma":[0.00008477442,0.0001023274,0.0001169144,0.00007298485,0.00009710152,0.0002331005,0.0001348477,0.0002678983,0.0001149742],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001098107,"about_ca_system_score_gemma":0.00006579026,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001145329,"about_ca_topic_score_gemma":0.0002801896,"domain_scores_codex":[0.9999589,0.000005119439,0.000001832026,0.00001235764,0.00001082096,0.00001099089],"domain_scores_gemma":[0.999939,0.00001115531,0.00002213945,0.000005402005,0.000006012979,0.00001638403],"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":[0.0000207044,0.000008780318,0.00001928779,0.00002154004,0.000002392854,0.00004110622,0.00000630332,0.0001190091,0.9987551,0.00009433548,0.00002298223,0.0008884656],"study_design_scores_gemma":[0.00001495443,0.0001533607,0.001156898,0.000003919155,0.00001482526,0.0001557485,0.000009478238,0.001799777,0.9948397,0.00005514524,0.001791974,0.000004171938],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9857552,0.00107663,0.01031924,0.00006966238,0.00007038734,0.00002634486,0.0001231915,0.0001143306,0.0024451],"genre_scores_gemma":[0.991392,0.0004706825,0.005990467,0.00005067268,0.00001580611,0.00001521425,0.00007474944,0.00001944066,0.00197099],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006191272,"threshold_uncertainty_score":0.002071142,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004334628944658391,"score_gpt":0.2035137916073509,"score_spread":0.1991791626626926,"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."}}