{"id":"W4281491410","doi":"10.1515/bmt-2022-0017","title":"Non-woven textiles for medical implants: mechanical performances improvement","year":2022,"lang":"en","type":"article","venue":"Biomedizinische Technik/Biomedical Engineering","topic":"Electrospun Nanofibers in Biomedical Applications","field":"Materials Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Hôpital Saint-François d'Assise; Centre hospitalier universitaire de Québec","funders":"","keywords":"Image stitching; Reinforcement; Ultimate tensile strength; Materials science; Composite material; Textile; Weaving; Yarn; Woven fabric; Structural engineering; Computer science; 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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002738571,0.0004960221,0.0006549865,0.0005166599,0.000690748,0.00007536971,0.002058758,0.0004079446,0.002511348],"category_scores_gemma":[0.0002641864,0.000447223,0.0002505492,0.001307258,0.0004431979,0.0001726643,0.001209053,0.0007772085,0.000103409],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003531043,"about_ca_system_score_gemma":0.0004365959,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002366765,"about_ca_topic_score_gemma":0.000001487008,"domain_scores_codex":[0.9938037,0.00003386221,0.001159013,0.001000825,0.002608584,0.001393962],"domain_scores_gemma":[0.9975662,0.0004668754,0.0002438725,0.0007201402,0.0000850811,0.0009178569],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006004262,0.0004325984,0.000005446082,0.0001699092,0.00004489202,0.00002255394,0.00006502902,0.00001028699,0.9627917,0.003473885,0.01799303,0.01493059],"study_design_scores_gemma":[0.002173005,0.001800743,0.0000408967,0.00009459193,0.00007302106,0.0002685317,0.0001781573,0.03120704,0.3048362,0.0006257282,0.6577737,0.0009284503],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2189217,0.0009408511,0.7441993,0.01492622,0.008102381,0.005572419,0.002100033,0.004564228,0.0006728361],"genre_scores_gemma":[0.8949347,0.0001098145,0.09232388,0.001388203,0.001674241,0.008410231,0.0006874262,0.0001970828,0.0002744729],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6760129,"threshold_uncertainty_score":0.9997979,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005636584656987148,"score_gpt":0.2404658272299753,"score_spread":0.2348292425729881,"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."}}