{"id":"W341848956","doi":"10.1016/b978-1-78242-017-0.00005-2","title":"Nanofibers for ligament and tendon tissue regeneration","year":2015,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Electrospun Nanofibers in Biomedical Applications","field":"Materials Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Flexibility (engineering); Nanofiber; Ligament; Regeneration (biology); Fabrication; Materials science; Tendon; Tissue engineering; Nanotechnology; Biomedical engineering; Engineering; Anatomy; Medicine; Biology; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001498971,0.0008936444,0.0002853971,0.001146219,0.0002474904,0.0006628105,0.0003293612,0.000835493,0.01811888],"category_scores_gemma":[0.0001032628,0.0002418899,0.00027608,0.0007343909,0.0002066442,0.001618478,0.0004676467,0.0007596597,0.005198097],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000348099,"about_ca_system_score_gemma":0.00016505,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003355989,"about_ca_topic_score_gemma":0.001085556,"domain_scores_codex":[0.9999301,0.000003587952,0.000004205071,0.00001496646,0.00004066049,0.00000645326],"domain_scores_gemma":[0.999972,0.0000102399,0.000004687862,0.000002259305,0.000007807491,0.000003112211],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00005038969,0.0001349002,0.00005376732,0.001848608,0.00002426631,0.0003827858,0.0001187799,0.00149157,0.2388688,0.02235581,0.02956353,0.7051069],"study_design_scores_gemma":[0.00001328661,0.0001132459,0.0004550925,0.0005560971,0.00002550011,0.001182291,0.00006744062,0.001654066,0.1070801,0.01364919,0.8751687,0.00003491167],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"other","genre_gemma":"methods","genre_scores_codex":[0.02339719,0.4396243,0.06193024,0.001641641,0.005138892,0.0001077519,0.0004512155,0.0007928244,0.4669159],"genre_scores_gemma":[0.0412688,0.1614312,0.02329153,0.0008274349,0.00141217,0.0001001535,0.0003658459,0.0002137828,0.7710891],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.01811888,"threshold_uncertainty_score":0.06061369,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02160872309810902,"score_gpt":0.2731643078799056,"score_spread":0.2515555847817966,"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."}}