{"id":"W2565127484","doi":"10.1016/j.biomaterials.2016.12.026","title":"Sequentially-crosslinked bioactive hydrogels as nano-patterned substrates with customizable stiffness and degradation for corneal tissue engineering applications","year":2016,"lang":"en","type":"article","venue":"Biomaterials","topic":"Corneal Surgery and Treatments","field":"Medicine","cited_by":230,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Institute of Materials Research and Engineering; Mechanobiology Institute, Singapore","keywords":"Self-healing hydrogels; Materials science; Gelatin; Tissue engineering; Biomedical engineering; Nanotechnology; Corneal endothelium; Monolayer; Cornea; Chemistry; Polymer chemistry","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":[0.0001965284,0.0004043398,0.0001421523,0.0001702949,0.00009854531,0.0002784578,0.0001694797,0.000356502,0.0008880917],"category_scores_gemma":[0.0001968835,0.0002661308,0.0001777931,0.0001384759,0.0001674612,0.0003550436,0.0001697706,0.0003334304,0.0002122497],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002062032,"about_ca_system_score_gemma":0.0002187952,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003264233,"about_ca_topic_score_gemma":0.001649572,"domain_scores_codex":[0.9998908,0.00001128661,0.00001223764,0.00002295062,0.00003438488,0.00002831702],"domain_scores_gemma":[0.9998575,0.00003349396,0.00005121989,0.0000139818,0.00001874832,0.00002501525],"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":[0.00001546697,0.000005731305,0.00002825412,0.00001966874,0.000001431542,0.00001444904,0.0000063765,0.00007766649,0.9991968,0.00002604066,0.00001324311,0.0005948499],"study_design_scores_gemma":[0.000008645962,0.00005843235,0.0007360028,0.0000042556,0.000009278586,0.00005699031,0.00001261006,0.0007909308,0.9975832,0.00002305339,0.0007102364,0.000006415416],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9817076,0.003033983,0.01181904,0.0001029286,0.0001228391,0.00004544244,0.0002976151,0.0001167589,0.002753664],"genre_scores_gemma":[0.9845492,0.001186498,0.01177542,0.000111088,0.00002131414,0.0000660572,0.0001629281,0.00004496963,0.002082407],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008880917,"threshold_uncertainty_score":0.002970934,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01774591577121878,"score_gpt":0.2700413813145811,"score_spread":0.2522954655433623,"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."}}