{"id":"W2899019511","doi":"10.1039/c8se00452h","title":"Alkali–oxygen treatment prior to the mechanical pulping of hardwood enhances enzymatic hydrolysis and carbohydrate recovery through selective lignin modification","year":2018,"lang":"en","type":"article","venue":"Sustainable Energy & Fuels","topic":"Biofuel production and bioconversion","field":"Engineering","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Korea Institute of Science and Technology","keywords":"Lignin; Enzymatic hydrolysis; Hydrolysis; Carbohydrate; Hardwood; Chemistry; Pulp (tooth); Pulp and paper industry; Alkali metal; Organic chemistry; Botany; Medicine; Biology; Engineering; Dentistry","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":[0.00008218794,0.0003395951,0.0001419226,0.0001519227,0.0001108318,0.000250197,0.0002239638,0.0001996282,0.001459523],"category_scores_gemma":[0.00008883501,0.0001142997,0.0001588265,0.0001556228,0.0001356335,0.0002999645,0.0001694948,0.0003921958,0.0001994718],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001313523,"about_ca_system_score_gemma":0.0001550161,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005438275,"about_ca_topic_score_gemma":0.002146181,"domain_scores_codex":[0.9999247,0.000003694909,0.000004612193,0.00001941024,0.0000250343,0.0000225155],"domain_scores_gemma":[0.9999533,0.00000765238,0.00001491371,0.000005698677,0.000008027898,0.00001051206],"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":[0.00002639558,0.0000135317,0.00005913927,0.00002309908,0.000001723057,0.00001192019,0.000004421289,0.00002951378,0.9982844,0.0000483915,0.00001241747,0.001485141],"study_design_scores_gemma":[0.000002090581,0.00003432134,0.0006713193,9.894492e-7,0.000002733396,0.00001743177,0.000004613372,0.0001811108,0.9986441,0.00001056267,0.000429149,0.000001581939],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9903369,0.0004352726,0.006886924,0.00004236201,0.00002960412,0.00002263981,0.0001117445,0.00005287324,0.002081658],"genre_scores_gemma":[0.9934253,0.0003395225,0.00288635,0.00003556569,0.000007565919,0.00001104432,0.0001392866,0.0000168878,0.003138468],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001459523,"threshold_uncertainty_score":0.004882574,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00981855448608246,"score_gpt":0.2213585648847387,"score_spread":0.2115400103986562,"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."}}