{"id":"W3159071263","doi":"10.1039/d1gc00738f","title":"Eco-friendly additives in acidic pretreatment to boost enzymatic saccharification of hardwood for sustainable biorefinery applications","year":2021,"lang":"en","type":"article","venue":"Green Chemistry","topic":"Biofuel production and bioconversion","field":"Engineering","cited_by":119,"is_retracted":false,"has_abstract":true,"ca_institutions":"Calgary Laboratory Services; University of Calgary","funders":"Priority Academic Program Development of Jiangsu Higher Education Institutions; National Natural Science Foundation of China","keywords":"Biorefinery; Hardwood; Environmentally friendly; Chemistry; Enzymatic hydrolysis; Pulp and paper industry; Hydrolysis; Organic chemistry; Botany; Raw material; Engineering; Biology; Ecology","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":[0.0001166548,0.0006218561,0.000211199,0.0002984341,0.0001817417,0.0003576057,0.000219563,0.0003231883,0.001286495],"category_scores_gemma":[0.0001053593,0.0001499745,0.000289755,0.000165334,0.0001283454,0.0004483962,0.0002650756,0.0006106013,0.0004992963],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000158259,"about_ca_system_score_gemma":0.0002346727,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004388215,"about_ca_topic_score_gemma":0.001609729,"domain_scores_codex":[0.9998885,0.00001167361,0.000008265726,0.00001815252,0.00004197018,0.00003139595],"domain_scores_gemma":[0.999948,0.000005994408,0.00001070067,0.000003824198,0.00002060282,0.00001074593],"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":[0.00005880748,0.00004576556,0.00008716542,0.00008858266,0.000007826981,0.000102253,0.0000129111,0.0003763835,0.9939815,0.0003560271,0.00006839284,0.00481431],"study_design_scores_gemma":[0.000002821398,0.00007709472,0.0001892078,0.000005399051,0.00001284423,0.00004091183,0.00001060497,0.0009004506,0.9953498,0.0000474419,0.003358839,0.000004518913],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9394115,0.007972741,0.03959767,0.0004092148,0.0003022778,0.0001066358,0.0002846975,0.0002974189,0.01161788],"genre_scores_gemma":[0.9822875,0.002356571,0.008531705,0.0001105027,0.00004166551,0.0000197656,0.0001211051,0.00003972881,0.006491411],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001286495,"threshold_uncertainty_score":0.004303813,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007609995946093487,"score_gpt":0.2136281315825346,"score_spread":0.2060181356364411,"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."}}