{"id":"W2062608800","doi":"10.1002/adfm.201303655","title":"Composite Living Fibers for Creating Tissue Constructs Using Textile Techniques","year":2014,"lang":"en","type":"article","venue":"Advanced Functional Materials","topic":"3D Printing in Biomedical Research","field":"Engineering","cited_by":160,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; McGill University and Génome Québec Innovation Centre","funders":"National Institute of Dental and Craniofacial Research; National Institute of Biomedical Imaging and Bioengineering; National Institute of Arthritis and Musculoskeletal and Skin Diseases; National Heart, Lung, and Blood Institute; National Institutes of Health; National Science Foundation","keywords":"Materials science; Weaving; Fabrication; Prepolymer; Composite number; Textile; Tissue engineering; Composite material; Polymer; Thread (computing); Nanotechnology; Mechanical engineering; Biomedical engineering; Polyurethane; Engineering","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":[0.0004531253,0.0001494757,0.0002200423,0.00009505035,0.0001567082,0.00007383108,0.0001120882,0.00009269313,0.0004332082],"category_scores_gemma":[0.0006146301,0.0001535092,0.0000289713,0.0001039531,0.00008189382,0.0001563022,0.00006257072,0.00008076843,0.00002621562],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009028064,"about_ca_system_score_gemma":0.0000175296,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000848712,"about_ca_topic_score_gemma":7.390144e-7,"domain_scores_codex":[0.9989116,0.00004210967,0.0002906921,0.000208392,0.0002169354,0.0003302864],"domain_scores_gemma":[0.9987964,0.000810412,0.00005209891,0.0001587453,0.00009756179,0.00008480441],"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":[0.00001954565,0.000005748253,0.00003922612,0.0001645811,0.00001717811,3.737584e-7,0.00001744339,0.001927694,0.9669555,0.0007869124,0.0001079756,0.02995786],"study_design_scores_gemma":[0.0001725964,0.00006347768,0.0006165622,0.0002702373,0.00001030856,0.00001521853,0.00001237771,0.005487454,0.9836527,0.002357809,0.007134216,0.0002070882],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7534096,0.00005481196,0.2414844,0.00002637187,0.001279568,0.0004428371,0.00005399832,0.0006821062,0.002566366],"genre_scores_gemma":[0.8325635,0.000007429884,0.1666974,0.00004276661,0.00042473,0.00007770882,0.0000286145,0.00004671821,0.0001112143],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0791539,"threshold_uncertainty_score":0.6259925,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01662223026675951,"score_gpt":0.281966861897877,"score_spread":0.2653446316311174,"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."}}