{"id":"W4385304513","doi":"10.1016/j.biortech.2023.129579","title":"The coupling effects between acid-catalyzed hydrothermal pretreatment and acidic/alkaline deep eutectic solvent extraction for wheat straw fractionation","year":2023,"lang":"en","type":"article","venue":"Bioresource Technology","topic":"Catalysis for Biomass Conversion","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"Department of Science and Technology of Sichuan Province; Ministry of Science and Technology of the People's Republic of China","keywords":"Choline chloride; Chemistry; Hemicellulose; Lignin; Fractionation; Deep eutectic solvent; Cellulose; Extraction (chemistry); Sodium hydroxide; Hydroxide; Chloride; Catalysis; Nuclear chemistry; Organic chemistry; Inorganic chemistry; Eutectic system","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":[0.0001594132,0.0003465135,0.0002395406,0.0001574113,0.0001399158,0.000252167,0.0002105817,0.0002923607,0.001022251],"category_scores_gemma":[0.0002265264,0.0002045459,0.0002481553,0.0001940527,0.0001929573,0.0004912063,0.0002141463,0.0004402578,0.0003088258],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002195666,"about_ca_system_score_gemma":0.0002518914,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001063816,"about_ca_topic_score_gemma":0.003019294,"domain_scores_codex":[0.9999142,0.000009850347,0.000007841879,0.00001904767,0.00002025011,0.00002882676],"domain_scores_gemma":[0.9999415,0.00001632213,0.00001423567,0.000004487571,0.00001291977,0.00001068946],"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":[0.0001945668,0.00002358821,0.000146934,0.00008975685,0.00001013464,0.00004040129,0.00002243084,0.0001299354,0.9954423,0.00009766336,0.00004888976,0.003753499],"study_design_scores_gemma":[0.000009939716,0.0001261397,0.001159249,0.00000345386,0.00002257535,0.00004264039,0.00001790683,0.0007780605,0.9970598,0.00002469282,0.0007479969,0.000007489973],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9902953,0.002338884,0.004796092,0.00007477107,0.00007476386,0.00003266927,0.0001092683,0.00005068299,0.002227617],"genre_scores_gemma":[0.996623,0.0008451128,0.001328888,0.00003837932,0.00001149381,0.00001061825,0.00006661339,0.00001043824,0.001065328],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001063816,"threshold_uncertainty_score":0.003419757,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008127042315335509,"score_gpt":0.236879296027256,"score_spread":0.2287522537119205,"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."}}