{"id":"W4389276240","doi":"10.59717/j.xinn-mater.2023.100040","title":"All-cellulose hydrogel-based adhesive","year":2023,"lang":"en","type":"article","venue":"The Innovation Materials","topic":"Advanced Cellulose Research Studies","field":"Materials Science","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Graduate School, University of Maryland; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Maryland Advanced Research Computing Center; Division of Civil, Mechanical and Manufacturing Innovation; National Science Foundation","keywords":"Cellulose; Self-healing hydrogels; Adhesive; Materials science; Adhesion; Polymer; Chemical engineering; Substrate (aquarium); Polymer science; Polymer chemistry; Nanotechnology; Composite material; Layer (electronics)","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":[0.00008899492,0.0003657577,0.0001101004,0.0001853901,0.0001058816,0.0001784523,0.0002399947,0.0001915365,0.002289369],"category_scores_gemma":[0.0001009724,0.0001090309,0.0001188934,0.0001388609,0.00008379092,0.0002847084,0.0001749102,0.0002693736,0.0007419258],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002256043,"about_ca_system_score_gemma":0.0002172387,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000398598,"about_ca_topic_score_gemma":0.001314581,"domain_scores_codex":[0.9999014,0.000007643668,0.00000791397,0.0000267295,0.00003913019,0.00001722403],"domain_scores_gemma":[0.9999319,0.0000114444,0.00002391602,0.000006582189,0.00001120165,0.00001489859],"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":[0.000007752708,0.000008644507,0.00005481837,0.00008643803,0.000002758259,0.00005216812,0.0000053002,0.0001054189,0.9952812,0.0001895023,0.0001707928,0.004035369],"study_design_scores_gemma":[0.00000322098,0.00004623314,0.0004117902,0.000006485019,0.000005744965,0.0001590611,0.000004411624,0.000671309,0.9927515,0.00002719218,0.005908945,0.000004102476],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8857121,0.01838857,0.05713285,0.0005065297,0.000543595,0.0001715276,0.001599655,0.0009211261,0.0350241],"genre_scores_gemma":[0.9373486,0.006050395,0.04213396,0.0002755843,0.00006161761,0.00006343324,0.0006383824,0.00006812861,0.01336004],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002289369,"threshold_uncertainty_score":0.00765866,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06183818673602197,"score_gpt":0.3367808375667316,"score_spread":0.2749426508307096,"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."}}