{"id":"W2751038928","doi":"10.1016/j.biortech.2017.08.186","title":"Formulation of an optimized synergistic enzyme cocktail, HoloMix, for effective degradation of various pre-treated hardwoods","year":2017,"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 British Columbia","funders":"National Science Foundation, United Arab Emirates; National Research Foundation","keywords":"Hydrolysis; Chemistry; Hardwood; Sodium chlorite; Lignin; Xylose; Xylanase; Biomass (ecology); Laccase; Enzymatic hydrolysis; Pulp and paper industry; Reducing sugar; Steam explosion; Food science; Sugar; Enzyme; Biochemistry; Botany; Agronomy; Fermentation; Organic chemistry; Biology","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":[0.0001601831,0.000133207,0.0002659642,0.0002737514,0.0001105844,0.00001215998,0.0002493274,0.0003441171,0.000009464336],"category_scores_gemma":[0.0001800585,0.0001240615,0.00006195458,0.0001076556,0.0001676348,0.0001065714,0.0000433766,0.00009190533,0.000001918422],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004298715,"about_ca_system_score_gemma":0.000007747209,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005136501,"about_ca_topic_score_gemma":0.000004805241,"domain_scores_codex":[0.9992937,0.00001801242,0.0002592806,0.0001993428,0.00007473604,0.0001549176],"domain_scores_gemma":[0.9990909,0.00003278063,0.0002228092,0.0005174588,0.0001068745,0.00002922547],"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":[0.0005187286,0.0001589138,0.003215147,0.0005218129,0.0001555085,0.000001509379,0.0001124813,0.00345133,0.9402708,0.001153421,0.0002810992,0.05015918],"study_design_scores_gemma":[0.00159609,0.0004446389,0.006448742,0.00003429052,0.00007058955,0.000004409977,0.0000386899,0.0642364,0.9249533,0.0003073522,0.001715349,0.0001501007],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9748445,0.0001183886,0.023564,0.0001003071,0.0001426056,0.000726943,0.00004215942,0.00036917,0.00009189043],"genre_scores_gemma":[0.9944534,0.00001336729,0.005288186,0.00000267567,0.00002869123,0.00005589916,0.00006325254,0.00002166302,0.00007280692],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06078506,"threshold_uncertainty_score":0.5059079,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009388237406015887,"score_gpt":0.2420479662232667,"score_spread":0.2326597288172508,"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."}}