{"id":"W2980763124","doi":"10.1016/j.carbpol.2019.115486","title":"Self-healing stimuli-responsive cellulose nanocrystal hydrogels","year":2019,"lang":"en","type":"article","venue":"Carbohydrate Polymers","topic":"Hydrogels: synthesis, properties, applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":88,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo; CelluForce (Canada)","funders":"Natural Sciences and Engineering Research Council of Canada; Natural Science Foundation of Hunan Province; Canada Foundation for Innovation","keywords":"Self-healing hydrogels; Monomer; Nanocrystal; Materials science; Polymerization; Cellulose; Aqueous solution; Solvent; Chemical engineering; Carboxymethyl cellulose; Polymer chemistry; Chemistry; Nanotechnology; Polymer; Organic chemistry; Composite material; Sodium","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002070655,0.0003426463,0.0002897505,0.0001210142,0.0001269312,0.00005046521,0.0004236808,0.0002735287,0.0001719156],"category_scores_gemma":[0.00005572888,0.0003450858,0.0001950316,0.0002523457,0.000119808,0.00001208444,0.000188359,0.000162112,0.0004632188],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006531987,"about_ca_system_score_gemma":0.0002732448,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001108418,"about_ca_topic_score_gemma":0.000009044375,"domain_scores_codex":[0.9979214,0.0001487,0.0003699925,0.000732902,0.0002344625,0.0005925486],"domain_scores_gemma":[0.9985846,0.0000342831,0.0001505575,0.0008925173,0.00008992861,0.0002480977],"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":[0.00007955627,0.00006982352,0.0003156827,0.00003367197,0.000139183,0.000005387231,0.0002233097,0.0002293372,0.9974899,0.0000786199,0.0002078327,0.00112773],"study_design_scores_gemma":[0.0004989604,0.000143552,0.00005563218,0.00001726001,0.00006116593,0.00001253962,0.0001780823,0.00173175,0.9369025,0.00002195018,0.05991211,0.000464494],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9891571,0.002827237,0.0003043608,0.0002848445,0.0002952273,0.0006282232,0.00004833522,0.0001085622,0.006346078],"genre_scores_gemma":[0.9951419,0.0001265847,0.000705329,0.0005350931,0.0002051593,0.0001154813,0.0001244655,0.00009603933,0.002949977],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06058736,"threshold_uncertainty_score":0.9999001,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01091603039346346,"score_gpt":0.233322521657201,"score_spread":0.2224064912637376,"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."}}