{"id":"W2757766515","doi":"10.1016/j.carbpol.2017.09.078","title":"Water-Induced shape memory effect of nanocellulose papers from sisal cellulose nanofibers with graphene oxide","year":2017,"lang":"en","type":"article","venue":"Carbohydrate Polymers","topic":"Polymer composites and self-healing","field":"Materials Science","cited_by":64,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor","funders":"Natural Science Foundation of Guangxi Province; National Natural Science Foundation of China","keywords":"Nanofiber; Cellulose; Microcrystalline cellulose; Nanocomposite; SISAL; Materials science; Nanocellulose; Graphene; Ultimate tensile strength; Oxide; Shape-memory alloy; Composite material; Hydrogen bond; Shape-memory polymer; Chemical engineering; Modulus; Polymer; Nanotechnology; Chemistry; Organic chemistry; Molecule","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":[0.0001354951,0.0003888491,0.0001618196,0.0002543722,0.0001594293,0.0002454647,0.0002481667,0.0002548795,0.001282139],"category_scores_gemma":[0.0002240284,0.000135561,0.000247645,0.0001712012,0.0001956303,0.0003505178,0.0002084647,0.0003605794,0.0001815939],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002747261,"about_ca_system_score_gemma":0.0001321468,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005181185,"about_ca_topic_score_gemma":0.001186777,"domain_scores_codex":[0.9998963,0.000008138316,0.000007328681,0.00002471909,0.00002359747,0.00003999903],"domain_scores_gemma":[0.9998348,0.00003823782,0.00005549389,0.00001650543,0.00002085782,0.00003409964],"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":[0.00005849396,0.0000124835,0.00006360181,0.00002975923,0.000005435066,0.00004787857,0.00002698381,0.00006883615,0.998259,0.00007116837,0.00003059594,0.001325706],"study_design_scores_gemma":[0.00000256145,0.00002791929,0.0005109716,0.000001635248,0.00000388784,0.00001361081,0.000009083978,0.0002007357,0.9990115,0.00001127267,0.0002043941,0.000002272437],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9963048,0.0006687766,0.0008874683,0.00004687956,0.00004381861,0.000006896808,0.00006926882,0.00005389776,0.001918365],"genre_scores_gemma":[0.9981611,0.0001893039,0.0004956461,0.00002766353,0.000009086335,0.000004931921,0.0000539673,0.00001561013,0.001042658],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001282139,"threshold_uncertainty_score":0.00428915,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00962903618243322,"score_gpt":0.2215872044175551,"score_spread":0.2119581682351218,"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."}}