{"id":"W4390503170","doi":"10.1016/j.ijbiomac.2023.129138","title":"Integrated acetic acid and deep eutectic solvent pretreatment on poplar for co-production of xylo-oligosaccharides, fermentable sugars and lignin antioxidants/adsorbents","year":2024,"lang":"en","type":"article","venue":"International Journal of Biological Macromolecules","topic":"Biofuel production and bioconversion","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"Major Basic Research Project of the Natural Science Foundation of the Jiangsu Higher Education Institutions; Natural Science Research of Jiangsu Higher Education Institutions of China; Priority Academic Program Development of Jiangsu Higher Education Institutions; Natural Science Foundation of Jiangsu Province; National Natural Science Foundation of China","keywords":"Chemistry; Lignin; Lignocellulosic biomass; Cellulose; Hydrolysis; Hemicellulose; Biorefinery; Deep eutectic solvent; Biomass (ecology); Sawdust; Fractionation; Enzymatic hydrolysis; Organic chemistry; Acetic acid; Chromatography; Raw material; Eutectic system; Agronomy","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":[0.0002038107,0.0001338344,0.0001718127,0.0001760872,0.00002973095,0.0000553289,0.0001012679,0.0000852179,0.00002616137],"category_scores_gemma":[0.00006281211,0.00009202895,0.00007502871,0.00006501968,0.00007929309,0.00009163789,0.00002424414,0.0001358343,0.000002420035],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008748537,"about_ca_system_score_gemma":0.00001166644,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004579338,"about_ca_topic_score_gemma":8.157662e-7,"domain_scores_codex":[0.9992103,0.00002868156,0.0003062448,0.0001771181,0.000164892,0.0001127845],"domain_scores_gemma":[0.9996637,0.00003961876,0.00007625665,0.00004999687,0.0001142708,0.0000561502],"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":[0.0002622633,0.0001270015,0.001047106,0.0001167793,0.0003988614,0.00003950568,0.0001024503,0.00007864647,0.9781419,0.0002088081,0.0006397314,0.01883694],"study_design_scores_gemma":[0.0006144757,0.0009780701,0.001837525,0.0003277533,0.00005058401,0.0004454505,0.000209458,0.001852508,0.989907,0.001008687,0.002622617,0.0001458184],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9932715,0.003286062,0.001156776,0.0006517666,0.00135209,0.0001710289,0.00004369239,0.00003446861,0.00003267424],"genre_scores_gemma":[0.9953227,0.0032031,0.001261479,0.00003550198,0.00012028,0.000005102557,0.00002110091,0.000009516819,0.00002120685],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01869112,"threshold_uncertainty_score":0.3752832,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01918529484891984,"score_gpt":0.265939109218861,"score_spread":0.2467538143699412,"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."}}