{"id":"W4319036460","doi":"10.1002/bbb.2476","title":"Broadening the product portfolio with cellulose and lignin nanoparticles in an elephant grass biorefinery","year":2023,"lang":"en","type":"article","venue":"Biofuels Bioproducts and Biorefining","topic":"Lignin and Wood Chemistry","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Conselho Nacional de Desenvolvimento Científico e Tecnológico; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Fundação de Amparo à Pesquisa do Estado de São Paulo","keywords":"Biorefinery; Cellulose; Lignin; Pulp and paper industry; Xylose; Biomass (ecology); Lignocellulosic biomass; Chemistry; Pulp (tooth); Enzymatic hydrolysis; Raw material; Furfural; Hydrolysis; Organic chemistry; Fermentation; Agronomy","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003801639,0.0002906685,0.0002418276,0.0001582893,0.0001306788,0.000202796,0.0001536557,0.00008548513,0.000002126769],"category_scores_gemma":[0.00001925212,0.0001837147,0.00001938406,0.0008240481,0.0001948122,0.0002805876,0.00008922249,0.0002070222,0.000006553029],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001545575,"about_ca_system_score_gemma":0.00002266948,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004172343,"about_ca_topic_score_gemma":0.00002807479,"domain_scores_codex":[0.9984552,0.00002293509,0.0002800523,0.0005473833,0.0001774764,0.0005169484],"domain_scores_gemma":[0.9994175,0.00002806739,0.00004827388,0.0003454404,0.00003025214,0.0001305089],"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":[0.00001133092,0.00002327383,0.03443168,0.0001268579,0.00002238876,0.00005871295,0.0005003121,0.00001582543,0.9566257,0.00007476842,0.0006229855,0.007486139],"study_design_scores_gemma":[0.0003896072,0.00009546774,0.01912935,0.000110608,0.0000223649,0.00005627522,0.0005366968,0.0004592985,0.9774974,0.00005218622,0.001265557,0.0003851832],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9962962,0.002375534,5.385377e-7,0.0003998145,0.000127381,0.000156146,0.00001029638,0.0003747357,0.0002593731],"genre_scores_gemma":[0.9984684,0.0005331136,0.000367573,0.00004217169,0.000251308,0.00002516306,0.00002496119,0.00005014268,0.0002371505],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02087168,"threshold_uncertainty_score":0.7491669,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01294984119192594,"score_gpt":0.2061261188307093,"score_spread":0.1931762776387833,"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."}}