{"id":"W3006166428","doi":"10.1021/acssuschemeng.9b07791","title":"Efficient Fractionation of Corn Stover for Biorefinery Using a Sustainable Pathway","year":2020,"lang":"en","type":"article","venue":"ACS Sustainable Chemistry & Engineering","topic":"Catalysis for Biomass Conversion","field":"Engineering","cited_by":45,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"Taishan Scholar Project of Shandong Province; Natural Science Foundation of Shandong Province; Guangxi Key Laboratory of Clean Pulp and Papermaking and Pollution Control; State Key Laboratory of Heavy Oil Processing; National Natural Science Foundation of China","keywords":"Corn stover; Chemistry; Hydrolysate; Levulinic acid; Lignin; Hydrolysis; Cellulose; Xylose; Enzymatic hydrolysis; Biorefinery; Lignocellulosic biomass; Fractionation; Organic chemistry; Chromatography; Catalysis; Nuclear chemistry; Raw material; Fermentation","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001426897,0.0002592019,0.0002907101,0.0001023028,0.00007828468,0.00003772155,0.0001863294,0.000156087,0.00003719762],"category_scores_gemma":[0.0002656769,0.0003156654,0.0001426252,0.0006277324,0.00002281661,0.0001619707,0.0001021271,0.0001553345,0.000001879566],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005727772,"about_ca_system_score_gemma":0.00008897467,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002249179,"about_ca_topic_score_gemma":3.663025e-8,"domain_scores_codex":[0.9985765,0.00000318047,0.0003394077,0.0002797916,0.0002288264,0.0005723575],"domain_scores_gemma":[0.9991592,0.00007043894,0.00008180119,0.0002412088,0.0003049273,0.0001424863],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00001396754,0.00001250482,0.00001198755,0.001848188,0.00004286903,0.00001452816,0.0001261374,0.5097737,0.4877138,0.0002476378,0.000158534,0.00003619717],"study_design_scores_gemma":[0.0003391358,0.00001151345,0.000009681259,0.00001801313,0.0000319952,0.000004182752,0.001162897,0.4549102,0.528464,0.000009436118,0.01483144,0.0002074883],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9116967,0.0004036518,0.08658005,0.00007230195,0.00008122058,0.0003775793,0.00002637341,0.0003883699,0.0003737295],"genre_scores_gemma":[0.9978646,0.000004768581,0.00138972,0.00001483187,0.0001230795,0.00003955662,0.00008832361,0.00008109413,0.0003939974],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0861679,"threshold_uncertainty_score":0.9999295,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007080372155281218,"score_gpt":0.184171238118495,"score_spread":0.1770908659632138,"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."}}