{"id":"W4366982319","doi":"10.1021/acs.biomac.3c00152","title":"Self-Assembly of Nanocellulose Hydrogels Mimicking Bacterial Cellulose for Wound Dressing Applications","year":2023,"lang":"en","type":"article","venue":"Biomacromolecules","topic":"Advanced Cellulose Research Studies","field":"Materials Science","cited_by":75,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University of New Brunswick","funders":"Wallenberg Wood Science Center; Kempestiftelserna; Linköpings Universitet; Kempe Foundation; Luleå Tekniska Universitet; University of Toronto; Stiftelsen för Strategisk Forskning","keywords":"Nanocellulose; Self-healing hydrogels; Nanofiber; Cellulose; Bacterial cellulose; Materials science; Pulp (tooth); Wound dressing; Chemical engineering; Composite material; Chemistry; Polymer chemistry; Organic chemistry","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":[0.0001172276,0.0002276842,0.000121639,0.0001238368,0.00007502988,0.0001456299,0.0001134545,0.0001526628,0.0004234423],"category_scores_gemma":[0.0001309808,0.00006900915,0.0001458078,0.00009581947,0.00006723891,0.0001695353,0.00009256639,0.0002093928,0.0001218702],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002250828,"about_ca_system_score_gemma":0.0001633768,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007907467,"about_ca_topic_score_gemma":0.001841993,"domain_scores_codex":[0.9999423,0.00000585433,0.000004903026,0.00001159316,0.00001878137,0.00001652126],"domain_scores_gemma":[0.9999348,0.00001232522,0.00001645248,0.000006135801,0.00001204521,0.00001824825],"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":[0.00001091718,0.000006650597,0.00002648317,0.00001192416,0.000001092023,0.00001196618,0.000003374543,0.0001075664,0.998987,0.00002207333,0.000006857746,0.0008041286],"study_design_scores_gemma":[0.00000204187,0.00004871148,0.0003737517,0.000001760031,0.000002449099,0.00002302366,0.000004167513,0.0009088763,0.9982013,0.000009375241,0.00042278,0.000001733607],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9847687,0.001409865,0.01148233,0.00004816123,0.00003866935,0.00005873137,0.0001578787,0.00007978657,0.001955908],"genre_scores_gemma":[0.987392,0.0005946246,0.01057537,0.00003246603,0.000006723119,0.00002837571,0.00008924188,0.00001589904,0.001265257],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007907467,"threshold_uncertainty_score":0.001633108,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02605870455294453,"score_gpt":0.3061005849204427,"score_spread":0.2800418803674982,"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."}}