{"id":"W4412438212","doi":"10.1016/j.scenv.2025.100268","title":"Production and valorization of acetic acid from lignocellulosic biomass pyrolysis: Influence of operational conditions and membrane separation processes","year":2025,"lang":"en","type":"article","venue":"Sustainable Chemistry for the Environment","topic":"Thermochemical Biomass Conversion Processes","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"Institut national de la recherche scientifique; Ministère de l'Agriculture, des Pêcheries et de l'Alimentation","keywords":"Lignocellulosic biomass; Biomass (ecology); Pulp and paper industry; Acetic acid; Pyrolysis; Chemistry; Biofuel; Production (economics); Waste management; Environmental science; Lignin; Agronomy; Organic chemistry; Engineering; Biology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005417237,0.0006495168,0.0006276276,0.0003860204,0.0001608876,0.0005889112,0.0003588918,0.0004673103,0.0004348037],"category_scores_gemma":[0.0003574391,0.0002836026,0.000721053,0.0005655174,0.0001922286,0.0008999338,0.0003295194,0.0007836456,0.0003671178],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003868442,"about_ca_system_score_gemma":0.0003667073,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006911235,"about_ca_topic_score_gemma":0.001180325,"domain_scores_codex":[0.9996814,0.00005754949,0.00003969038,0.00006531643,0.00009295651,0.00006316573],"domain_scores_gemma":[0.999923,0.0000271757,0.00001985615,0.000004857715,0.00001525281,0.00000985596],"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":[0.0001377778,0.00008379587,0.0003863907,0.003875898,0.00009471656,0.0003091391,0.00004994041,0.001478456,0.9627185,0.000697188,0.0002523343,0.02991582],"study_design_scores_gemma":[0.00002397827,0.0003954145,0.003091565,0.0003202772,0.0001747284,0.0004232601,0.00007783122,0.002413533,0.9730827,0.0003572232,0.0195979,0.0000416059],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.587792,0.3879699,0.01390624,0.0005649541,0.0002223281,0.0001157122,0.0005663413,0.0001226267,0.008739906],"genre_scores_gemma":[0.7208784,0.2648289,0.01135399,0.0001877046,0.00007693567,0.00009970011,0.0004874734,0.00005114718,0.002035837],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006911235,"threshold_uncertainty_score":0.002864897,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00327720894969263,"score_gpt":0.1946631099761351,"score_spread":0.1913859010264425,"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."}}