{"id":"W2978025379","doi":"10.1016/j.biortech.2019.122216","title":"Improving enzymatic saccharification of hardwood through lignin modification by carbocation scavengers and the underlying mechanisms","year":2019,"lang":"en","type":"article","venue":"Bioresource Technology","topic":"Biofuel production and bioconversion","field":"Engineering","cited_by":37,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"Priority Academic Program Development of Jiangsu Higher Education Institutions; Jiangsu University; National Natural Science Foundation of China","keywords":"Lignin; Chemistry; Hardwood; Carbocation; Enzymatic hydrolysis; Hydrolysis; Cellulose; Organic chemistry; Biomass (ecology); Scavenger; Botany; Agronomy; Radical","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":[0.000205752,0.0004430995,0.0001673593,0.0001352071,0.0001227805,0.0003696249,0.0002744345,0.0002842677,0.0005640556],"category_scores_gemma":[0.0001121258,0.00009854466,0.0002672774,0.0001375069,0.0002552081,0.0004749845,0.0002014508,0.0004139006,0.000141639],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003190649,"about_ca_system_score_gemma":0.0002645492,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008091527,"about_ca_topic_score_gemma":0.001333821,"domain_scores_codex":[0.9999177,0.000007210022,0.000005294055,0.00001610536,0.00002024227,0.00003339993],"domain_scores_gemma":[0.9999536,0.00000713441,0.00001364453,0.000005260695,0.00001185775,0.000008609543],"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":[0.00006099665,0.00003297446,0.0002257762,0.00008898266,0.000009727312,0.00004306402,0.0000202188,0.0002375556,0.9939353,0.000726522,0.00003684156,0.004582106],"study_design_scores_gemma":[0.000005157164,0.00009437236,0.0009481322,0.000004615548,0.00001723974,0.00004859161,0.0000257344,0.00118728,0.9959215,0.000178546,0.00156204,0.000006828016],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9781401,0.007998206,0.01110237,0.0002536913,0.00004937566,0.0000301891,0.00008960983,0.00006030468,0.002276263],"genre_scores_gemma":[0.9948814,0.002001795,0.001577814,0.00004006915,0.000008179421,0.000008931364,0.00006589147,0.000005684337,0.001410274],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008091527,"threshold_uncertainty_score":0.002314985,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01070167741256978,"score_gpt":0.2040714810964925,"score_spread":0.1933698036839227,"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."}}