{"id":"W4410221459","doi":"10.1088/1748-605x/add6f9","title":"Investigation of novel carboxymethyl chitosan-based bioinks for 3D bioprinting of neural tissues","year":2025,"lang":"en","type":"article","venue":"Biomedical Materials","topic":"3D Printing in Biomedical Research","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada; Universidade de São Paulo; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Canadian Institutes of Health Research; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Escola Politécnica da Universidade de São Paulo","keywords":"3D bioprinting; Biocompatibility; Biomedical engineering; Tissue engineering; Extracellular matrix; Materials science; Chitosan; Viability assay; Self-healing hydrogels; Cell; Biophysics; Chemistry; Biochemistry; Polymer chemistry; Biology","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":[0.00088573,0.0001533507,0.0004483272,0.0003905959,0.00002768256,0.00001884578,0.0003107202,0.0002395327,0.0000579461],"category_scores_gemma":[0.001888759,0.0001354484,0.0000634952,0.0005305955,0.0005536802,0.00003592787,0.00008904006,0.00009368698,0.000001658952],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002861144,"about_ca_system_score_gemma":0.00009848429,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004796821,"about_ca_topic_score_gemma":7.138381e-7,"domain_scores_codex":[0.9982889,0.00005329485,0.0007693958,0.000206684,0.0003712054,0.0003105232],"domain_scores_gemma":[0.9988089,0.0006170225,0.0001111106,0.0002441093,0.0001028592,0.0001160289],"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":[0.00002300348,0.00002328872,0.0001179012,0.002477929,0.00005607984,4.615563e-7,0.00004327801,0.00003245294,0.9872658,0.0004139279,0.0001578946,0.00938796],"study_design_scores_gemma":[0.0006871023,0.00006988516,0.001413357,0.0004923794,0.0000217003,3.850326e-7,0.00001460935,0.02086031,0.9754794,0.0001610985,0.0006948942,0.0001049088],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9771153,0.0002267862,0.02002957,0.0004893497,0.001392691,0.000391017,0.0001345991,0.0001424145,0.00007830491],"genre_scores_gemma":[0.9580556,0.00001471494,0.04159344,0.00004186451,0.0001472957,0.00005361998,0.00005907399,0.00002310377,0.00001131875],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02156387,"threshold_uncertainty_score":0.5523424,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03285618397052757,"score_gpt":0.3048072085593956,"score_spread":0.2719510245888681,"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."}}