{"id":"W4226434188","doi":"10.1177/20417314221086368","title":"In vitro maturation and in vivo stability of bioprinted human nasal cartilage","year":2022,"lang":"en","type":"article","venue":"Journal of Tissue Engineering","topic":"Osteoarthritis Treatment and Mechanisms","field":"Medicine","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"Misericordia Community Hospital; University of Alberta","funders":"Institute of Musculoskeletal Health and Arthritis; Edmonton Civic Employees Charitable Assistance Fund; Natural Sciences and Engineering Research Council of Canada; University Hospital Foundation; Canada Foundation for Innovation; Alberta Cancer Foundation","keywords":"Cartilage; Tissue engineering; In vivo; 3D bioprinting; Biomedical engineering; Extracellular matrix; Nasal cartilages; Resorption; Medicine; Anatomy; Nose; Pathology; Rhinoplasty; Cell biology; Biology; Biotechnology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002217578,0.00005467236,0.0002005953,0.000198354,0.0000117004,0.00000331057,0.00002591095,0.00002011458,0.00008305712],"category_scores_gemma":[0.00002724286,0.00005394743,0.00002449529,0.0001097607,0.000005588515,0.0000763013,0.00002272403,0.0001693744,1.058332e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001022036,"about_ca_system_score_gemma":0.00001533063,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009782888,"about_ca_topic_score_gemma":0.000009121847,"domain_scores_codex":[0.9994427,0.00001570177,0.0002762011,0.00005365033,0.0001325926,0.00007917126],"domain_scores_gemma":[0.9998012,0.00001576403,0.00007276489,0.00005365433,0.00002068987,0.00003593666],"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":[0.0002531844,0.00006414424,0.0008765601,0.0000443021,0.000003918162,0.0001893679,0.0004481403,0.0001919333,0.9975886,0.00002226602,0.000003422918,0.0003141546],"study_design_scores_gemma":[0.001778358,0.000639901,0.003231302,0.00006015256,0.00001278635,0.00018339,0.0002502296,0.0001992946,0.9933121,0.00001562218,0.0002755665,0.00004135242],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9992024,0.0003810484,0.00004453253,0.00008630562,0.0001415523,0.0001123855,0.000003596673,0.000004015488,0.00002422157],"genre_scores_gemma":[0.9990522,0.000004953857,0.0008611513,0.000005152244,0.00003570727,0.000003370025,0.000001362242,0.00000722802,0.00002887755],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004276561,"threshold_uncertainty_score":0.2199912,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009377157402544273,"score_gpt":0.2451791627963792,"score_spread":0.235802005393835,"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."}}