{"id":"W2605254160","doi":"10.1088/1758-5090/aa6b15","title":"Biofabricated soft network composites for cartilage tissue engineering","year":2017,"lang":"en","type":"article","venue":"Biofabrication","topic":"Osteoarthritis Treatment and Mechanisms","field":"Medicine","cited_by":185,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"National Health and Medical Research Council; Australian Research Council","keywords":"Materials science; Viscoelasticity; Cartilage; Composite material; Tissue engineering; Self-healing hydrogels; Polycaprolactone; Biomedical engineering; Chondrocyte; Electrospinning; Soft tissue; Finite element method; Polymer; Structural engineering; Anatomy; Polymer chemistry; Surgery; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001447621,0.0003793251,0.00007411602,0.0002566648,0.00009977673,0.0001388328,0.0001119752,0.0003298976,0.001750047],"category_scores_gemma":[0.0001324771,0.0001161796,0.0001407712,0.0001386933,0.00009277477,0.0002589962,0.0001213792,0.0002723475,0.0004546935],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001870453,"about_ca_system_score_gemma":0.0000878096,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000239875,"about_ca_topic_score_gemma":0.0006843155,"domain_scores_codex":[0.9999301,0.000008870939,0.000005614169,0.00001541038,0.00003159686,0.000008397267],"domain_scores_gemma":[0.9999323,0.0000220367,0.00002542344,0.00000500246,0.0000087491,0.000006567894],"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":[0.000008771495,0.00001076084,0.0000372269,0.00007719015,0.000002395157,0.00002474002,0.000008445815,0.0006830619,0.9923766,0.0001961331,0.00006399533,0.006510784],"study_design_scores_gemma":[0.000009172088,0.000150186,0.0008933057,0.00002033791,0.00001034014,0.0001503009,0.00001095303,0.00884344,0.9812463,0.0002826901,0.008370801,0.00001218883],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7819238,0.01824029,0.1820367,0.0004074658,0.0004808356,0.0001845528,0.0009083172,0.001315193,0.01450284],"genre_scores_gemma":[0.916046,0.003880629,0.07212335,0.000122638,0.00005174988,0.000136333,0.0003568037,0.00009238857,0.00719014],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001750047,"threshold_uncertainty_score":0.005854487,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01981080693896819,"score_gpt":0.2759558791913872,"score_spread":0.256145072252419,"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."}}