{"id":"W2739023495","doi":"10.1186/s13068-017-0876-z","title":"Lignin valorization: lignin nanoparticles as high-value bio-additive for multifunctional nanocomposites","year":2017,"lang":"en","type":"article","venue":"Biotechnology for Biofuels","topic":"Lignin and Wood Chemistry","field":"Engineering","cited_by":347,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"State Key Laboratory of Polymer Materials Engineering; China Scholarship Council; State Key Laboratory of Bioreactor Engineering; Sichuan University; Simon Fraser University; National Natural Science Foundation of China","keywords":"Organosolv; Lignin; Nanocomposite; Biopolymer; Biorefinery; Materials science; Nanoparticle; Cellulose; Lignocellulosic biomass; Chemical engineering; Composite material; Polymer; Chemistry; Nanotechnology; Organic chemistry; Raw material","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":[0.0001037564,0.0004131127,0.00011314,0.0002177561,0.00009506354,0.0002494634,0.000163473,0.0003146521,0.0006286594],"category_scores_gemma":[0.0001149284,0.00017893,0.0002106228,0.000112265,0.0001166283,0.0002449333,0.00025922,0.0003752474,0.0002747544],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002231275,"about_ca_system_score_gemma":0.00007815432,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002375555,"about_ca_topic_score_gemma":0.0008219774,"domain_scores_codex":[0.9999089,0.00001056357,0.000006477977,0.00003047072,0.00002439151,0.00001911627],"domain_scores_gemma":[0.9999479,0.000007534268,0.00001565804,0.00000459137,0.00001163701,0.00001263778],"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":[0.00001078777,0.000007514989,0.000024354,0.00003756463,0.000002914988,0.00002082325,0.000007988519,0.00008122577,0.9986884,0.00007256353,0.00002439905,0.001021401],"study_design_scores_gemma":[0.000002562956,0.00004598415,0.0002781381,0.00000311367,0.00000699447,0.00003670896,0.000006264142,0.0007345278,0.9976931,0.00001993581,0.001170039,0.000002538252],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9711349,0.002444399,0.0200755,0.0001556268,0.00006591549,0.00005783562,0.0002202586,0.0003384099,0.005507155],"genre_scores_gemma":[0.9904006,0.000552125,0.006492476,0.00005454425,0.00001029399,0.00003121761,0.0001165068,0.00003175888,0.002310427],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006286594,"threshold_uncertainty_score":0.002103031,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01006963296965995,"score_gpt":0.2367106314884631,"score_spread":0.2266409985188031,"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."}}