{"id":"W4224986409","doi":"10.1016/j.jcis.2022.04.119","title":"Highly stretchable, elastic, antimicrobial conductive hydrogels with environment-adaptive adhesive property for health monitoring","year":2022,"lang":"en","type":"article","venue":"Journal of Colloid and Interface Science","topic":"Advanced Sensor and Energy Harvesting Materials","field":"Engineering","cited_by":37,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Foundation for Innovation","keywords":"Self-healing hydrogels; Materials science; Adhesive; Electrical conductor; Ionic bonding; Nanotechnology; Viscoelasticity; Polymer; Conductor; Conductive polymer; Composite material; Polymer chemistry; Chemistry; Layer (electronics); Ion","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":[0.0001553311,0.0003087231,0.0001099534,0.0001564838,0.00008304074,0.0001989455,0.0001646431,0.0003259634,0.0005205123],"category_scores_gemma":[0.0002523864,0.0001186915,0.0001124536,0.0001116099,0.0001102288,0.0002919317,0.0002218204,0.0003324096,0.0001271582],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001223478,"about_ca_system_score_gemma":0.00008061263,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009575827,"about_ca_topic_score_gemma":0.0003491482,"domain_scores_codex":[0.9999031,0.00001148657,0.000006258315,0.0000260662,0.0000295529,0.00002346954],"domain_scores_gemma":[0.9998516,0.00003124703,0.00005184347,0.000009918003,0.00002331224,0.00003202318],"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":[0.00002356716,0.000008566988,0.00005294608,0.00002892848,0.000002023255,0.00002933207,0.000009316041,0.00006473758,0.997451,0.00004464459,0.000045524,0.002239487],"study_design_scores_gemma":[0.000006241933,0.0001224812,0.0009548145,0.000004552473,0.000008349683,0.0001139551,0.00001300056,0.001102842,0.9966306,0.00002553868,0.001011028,0.000006546002],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9764291,0.003367591,0.01702959,0.0002114693,0.0001085867,0.00003262111,0.0002091448,0.0001689796,0.002442897],"genre_scores_gemma":[0.9904748,0.0006720943,0.006937854,0.0001300526,0.0000214459,0.00002809033,0.00007064319,0.00001303666,0.001651943],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0005205123,"threshold_uncertainty_score":0.00174123,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01548231125169296,"score_gpt":0.2375228945908703,"score_spread":0.2220405833391773,"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."}}