{"id":"W3012148527","doi":"10.1016/b978-0-12-804077-5.00013-0","title":"Lignocellulosic Materials for Biomedical Applications","year":2020,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced Cellulose Research Studies","field":"Materials Science","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Hemicellulose; Cellulose; Nanocellulose; Lignin; Nanotechnology; Bacterial cellulose; Biocompatibility; Tissue engineering; Lignocellulosic biomass; Biochemical engineering; Drug delivery; Materials science; Chemistry; Biomedical engineering; Engineering; 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":[0.0001512555,0.001058688,0.0003648611,0.001228995,0.0003182204,0.001640125,0.0005375384,0.0007055001,0.0787837],"category_scores_gemma":[0.000109549,0.0003260153,0.0003155663,0.001613734,0.000227977,0.001467431,0.000589304,0.0009273011,0.03420934],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005289135,"about_ca_system_score_gemma":0.0003539543,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00138211,"about_ca_topic_score_gemma":0.003827837,"domain_scores_codex":[0.9999332,0.000002753444,0.000002722006,0.000009692178,0.00004388021,0.00000769757],"domain_scores_gemma":[0.9999708,0.00001012146,0.000002529094,0.000004587707,0.000008001378,0.000004002805],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004870929,0.0001250328,0.00006188662,0.000972893,0.00001151963,0.0002900868,0.00009686121,0.000942575,0.09743009,0.02791335,0.0797203,0.7923865],"study_design_scores_gemma":[0.000004979387,0.00003103087,0.0002768998,0.0001960158,0.000008726454,0.0003233919,0.00004421342,0.0003628264,0.01660634,0.00584098,0.9762962,0.000008447618],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"review","genre_scores_codex":[0.006264666,0.08891744,0.01359602,0.0008565997,0.001812936,0.00005681759,0.0007792592,0.0004947777,0.8872215],"genre_scores_gemma":[0.006577433,0.03656929,0.003875779,0.0002288108,0.0001832918,0.00002313917,0.0005435996,0.000122204,0.9518764],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.0787837,"threshold_uncertainty_score":0.2635577,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02967062836195741,"score_gpt":0.2935453365533582,"score_spread":0.2638747081914009,"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."}}