{"id":"W3177956364","doi":"10.1039/d1tb01075a","title":"Tunable, conductive, self-healing, adhesive and injectable hydrogels for bioelectronics and tissue regeneration applications","year":2021,"lang":"en","type":"article","venue":"Journal of Materials Chemistry B","topic":"Advanced Sensor and Energy Harvesting Materials","field":"Engineering","cited_by":42,"is_retracted":false,"has_abstract":true,"ca_institutions":"ASTER","funders":"Science and Engineering Research Board","keywords":"Bioelectronics; Self-healing hydrogels; Materials science; Self-healing; Nanotechnology; Regeneration (biology); Adhesive; Conductive polymer; Electrical conductor; Electrically conductive; Electronics; Polymer; Composite material; Biosensor; Polymer chemistry; Engineering; Electrical engineering; Medicine","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":[0.0001531658,0.0003249039,0.00009197171,0.0002014032,0.00009217988,0.0002866335,0.0001692294,0.0002819782,0.002081872],"category_scores_gemma":[0.0001391439,0.0001164809,0.0001427163,0.0001306392,0.0001477393,0.0003326604,0.0002038732,0.0002768024,0.0006418824],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001010359,"about_ca_system_score_gemma":0.000112813,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006659111,"about_ca_topic_score_gemma":0.0002340053,"domain_scores_codex":[0.9999292,0.0000124578,0.000006857082,0.00001906731,0.00001848145,0.00001390117],"domain_scores_gemma":[0.9998997,0.00002900902,0.00003319933,0.000006483672,0.00001286754,0.00001859724],"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":[0.00001925626,0.00001082427,0.00006036828,0.00008483717,0.000002427358,0.00003190634,0.000007682375,0.00004351499,0.9955801,0.0001680375,0.00005373994,0.003937331],"study_design_scores_gemma":[0.000005029889,0.00009139002,0.0007241324,0.00001290054,0.000009961345,0.0002684141,0.00001218581,0.0003971749,0.9943424,0.00009691626,0.004033873,0.000005645944],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9274618,0.01649745,0.04194948,0.0003324139,0.0002135905,0.00008536488,0.000735227,0.0004303784,0.01229423],"genre_scores_gemma":[0.9744503,0.003095839,0.0148743,0.0002153206,0.00003827252,0.0000591507,0.0002564143,0.00004379292,0.006966691],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002081872,"threshold_uncertainty_score":0.006964564,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008714127237077297,"score_gpt":0.2305354351331378,"score_spread":0.2218213078960605,"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."}}