{"id":"W4384826796","doi":"10.32920/23709585.v1","title":"Biomass processing into ethanol: pretreatment, enzymatic hydrolysis, fermentation, rheology, and mixing","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Biofuel production and bioconversion","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Biomass (ecology); Biofuel; Raw material; Enzymatic hydrolysis; Fermentation; Pulp and paper industry; Lignocellulosic biomass; Commercialization; Ethanol fuel; Renewable energy; Rheology; Hydrolysis; Renewable fuels; Biotechnology; Chemistry; Waste management; Food science; Materials science; Agronomy; Engineering; Biochemistry; Business; Organic chemistry; Biology","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":[0.0004237302,0.0008234826,0.0008925773,0.0006882282,0.0002449373,0.001103694,0.0003421275,0.0006343258,0.002207279],"category_scores_gemma":[0.0002689738,0.0004001946,0.0005446832,0.0009365206,0.000404367,0.001216506,0.0004426803,0.001188404,0.002317136],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004700887,"about_ca_system_score_gemma":0.0004509006,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004230518,"about_ca_topic_score_gemma":0.0006872794,"domain_scores_codex":[0.9997005,0.00002738333,0.00002833884,0.0000689165,0.0001417861,0.00003297781],"domain_scores_gemma":[0.9999367,0.00001635106,0.0000135336,0.000007155836,0.00002022249,0.000005905426],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001449148,0.0001606792,0.00051396,0.009981707,0.00008628015,0.0006028883,0.0002421301,0.002973505,0.4376395,0.01718617,0.004672807,0.5257955],"study_design_scores_gemma":[0.00001647743,0.0003308653,0.002162663,0.0006419859,0.00008217248,0.001481135,0.000175061,0.002498639,0.6010234,0.006411371,0.385112,0.00006412068],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.06099273,0.7808859,0.1088706,0.001555836,0.001727639,0.00020757,0.0004679257,0.0006257165,0.04466601],"genre_scores_gemma":[0.1737373,0.7320006,0.05816847,0.0007208673,0.0008190253,0.000172737,0.0009195227,0.0002563208,0.03320521],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002207279,"threshold_uncertainty_score":0.007384062,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02164832109711669,"score_gpt":0.257151632227249,"score_spread":0.2355033111301323,"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."}}