{"id":"W4229020758","doi":"10.1002/app.52520","title":"A green composite hydrogel based on xylan and lignin with adjustable mechanical properties, high swelling, excellent <scp>UV</scp> shielding, and antioxidation properties","year":2022,"lang":"en","type":"article","venue":"Journal of Applied Polymer Science","topic":"Hydrogels: synthesis, properties, applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"Natural Science Foundation of Shandong Province; Innovative Research Group Project of the National Natural Science Foundation of China","keywords":"Swelling; Materials science; Composite number; Lignin; Thermogravimetric analysis; Composite material; Self-healing hydrogels; Fourier transform infrared spectroscopy; Xylan; Toughness; Swelling capacity; Scanning electron microscope; Dynamic mechanical analysis; Polymer; Chemical engineering; Polymer chemistry; Chemistry; Polysaccharide; Organic chemistry","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":[0.0001041718,0.0002894444,0.0001501929,0.0002042762,0.00007742639,0.0001330512,0.0001130571,0.0001706855,0.0005640693],"category_scores_gemma":[0.00006670247,0.00008659208,0.00019429,0.0001264845,0.00009467435,0.000262522,0.0001466879,0.0001998484,0.0001100185],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000146142,"about_ca_system_score_gemma":0.0001283084,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001786222,"about_ca_topic_score_gemma":0.0006139366,"domain_scores_codex":[0.9999541,0.000004492373,0.000002864611,0.0000103135,0.00001673435,0.00001157626],"domain_scores_gemma":[0.9999418,0.000007317065,0.00001804042,0.000003270647,0.00001004737,0.0000195344],"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":[0.0000131375,0.000006209487,0.00003214322,0.0000244264,0.000002000991,0.00001896955,0.000002733367,0.00003993416,0.9989975,0.0000325828,0.00001008708,0.0008202667],"study_design_scores_gemma":[0.000008103494,0.0001161584,0.0006638221,0.00000335092,0.00001089629,0.0001190827,0.000005599803,0.0007407106,0.9975159,0.00002113039,0.0007910589,0.000004165101],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9812601,0.0021025,0.01490172,0.00009390234,0.00004952234,0.0000227196,0.0001954881,0.0001116765,0.001262421],"genre_scores_gemma":[0.9863551,0.0006326989,0.01098896,0.00006966504,0.00001390983,0.00001615071,0.0001356575,0.00001846526,0.001769426],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0005640693,"threshold_uncertainty_score":0.001887023,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01301112230908912,"score_gpt":0.2041714528111569,"score_spread":0.1911603305020677,"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."}}