{"id":"W2504713433","doi":"10.1007/978-3-319-14845-8_9","title":"Tissue Bank and Tissue Engineering","year":2016,"lang":"en","type":"book-chapter","venue":"Advanced structured materials","topic":"Tissue Engineering and Regenerative Medicine","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"National Institutes of Health; Université Laval","keywords":"Tissue engineering; Biomaterial; Process (computing); Tissue bank; Engineering; Scaffold; Biomedical engineering; Computer science; Medicine; Biochemical engineering; Risk analysis (engineering); Surgery","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00008242829,0.0006155256,0.00111229,0.000196866,0.00005263736,0.00002267475,0.00008875517,0.0004350918,0.001761641],"category_scores_gemma":[0.00007989468,0.0004330747,0.00004243268,0.00002228558,0.0001069681,0.00006136629,0.00006427829,0.0002375809,0.00005831563],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008109374,"about_ca_system_score_gemma":0.00003735381,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001623563,"about_ca_topic_score_gemma":7.844018e-7,"domain_scores_codex":[0.9983789,0.000008542957,0.0004547952,0.0005445995,0.0002649139,0.0003482707],"domain_scores_gemma":[0.9989972,0.00004979864,0.0001603157,0.0004590836,0.00008551045,0.000248071],"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":[0.00005914006,0.00000214852,4.630649e-7,0.000485483,0.0001235519,0.0001801909,0.00004799765,0.00001736987,0.9275759,0.03554644,0.0003457337,0.03561558],"study_design_scores_gemma":[0.001049576,0.0002627916,0.00007419646,0.001150494,0.0001590298,0.0003930135,0.000001799213,7.800178e-7,0.4568802,0.001243587,0.5383686,0.0004159632],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"review","genre_gemma":"other","genre_scores_codex":[0.1089747,0.3953421,0.06352752,0.01069902,0.07732404,0.02012764,0.007423146,0.007855747,0.3087261],"genre_scores_gemma":[0.07146604,0.001418795,0.01119915,0.00006581681,0.003313872,0.00003540604,0.0002254687,0.0003212174,0.9119542],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.6032282,"threshold_uncertainty_score":0.9998121,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007092469996956534,"score_gpt":0.2415237574716553,"score_spread":0.2344312874746987,"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."}}