{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004661914,0.0002683828,0.0001678791,0.0001979485,0.0001516358,0.0002710424,0.0001443683,0.0002780636,0.0007324946],"category_scores_gemma":[0.0004404828,0.0001590226,0.0002865294,0.0001563927,0.0002328584,0.0001824162,0.0001685026,0.0002514274,0.0002247292],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002208077,"about_ca_system_score_gemma":0.0001541469,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001378563,"about_ca_topic_score_gemma":0.001765113,"domain_scores_codex":[0.9997364,0.00004164128,0.00004535758,0.00005230632,0.00008731811,0.00003686381],"domain_scores_gemma":[0.9995565,0.000137009,0.0001042823,0.00006507413,0.0000922142,0.00004495567],"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":[0.00006815485,0.00002397888,0.0002127812,0.00002686221,0.000003718321,0.00004537962,0.00005780428,0.0001377679,0.9986609,0.0000146776,0.000009193598,0.0007387951],"study_design_scores_gemma":[0.000008780919,0.0006737302,0.008945262,0.00001193783,0.00002296129,0.0001760286,0.00006526674,0.000988544,0.987931,0.00001967487,0.001146632,0.00001020964],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9946581,0.001877829,0.001996824,0.0000167392,0.00002104409,0.00004015195,0.0002145717,0.0000168207,0.001157934],"genre_scores_gemma":[0.9953545,0.0006002806,0.002294955,0.00002553041,0.00000706884,0.00004759762,0.0003704736,0.00001390701,0.001285571],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001378563,"threshold_uncertainty_score":0.002741039,"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."}}