{"id":"W2953503724","doi":"10.1016/j.renene.2019.06.134","title":"Acidic and thermal pre-treatments for anaerobic digestion inoculum to improve hydrogen and volatile fatty acid production using xylose as the substrate","year":2019,"lang":"en","type":"article","venue":"Renewable Energy","topic":"Anaerobic Digestion and Biogas Production","field":"Engineering","cited_by":62,"is_retracted":false,"has_abstract":false,"ca_institutions":"National Research Council Canada","funders":"Fundação de Amparo à Pesquisa do Estado de São Paulo","keywords":"Xylose; Hydrogen production; Chemistry; Mesophile; Fermentative hydrogen production; Fermentation; Lignocellulosic biomass; Food science; Hydrogen; Anaerobic digestion; Biomass (ecology); Biofuel; Biochemistry; Biohydrogen; Organic chemistry; Bacteria; Biotechnology; Biology; Agronomy; Methane","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":[0.0001694851,0.0005251319,0.000359716,0.0002860918,0.000226254,0.0003691231,0.000249868,0.0002653509,0.001279384],"category_scores_gemma":[0.0002042002,0.0001761739,0.0003923156,0.0003341059,0.0001569488,0.0003036139,0.0002150333,0.000610565,0.0002093237],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001755143,"about_ca_system_score_gemma":0.0003694378,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001577008,"about_ca_topic_score_gemma":0.003949057,"domain_scores_codex":[0.9998301,0.00002166098,0.00002327588,0.00002818531,0.00005173118,0.00004498038],"domain_scores_gemma":[0.9999007,0.00001523384,0.00001864403,0.000006478623,0.00003434527,0.00002468631],"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":[0.0001866793,0.00006317511,0.0001735626,0.0000776647,0.000006632319,0.00003231618,0.00001767849,0.0001320266,0.9975163,0.00003656717,0.00004121038,0.001716184],"study_design_scores_gemma":[0.000006417639,0.0002115193,0.002179204,0.000007927591,0.00002138672,0.00003026638,0.00003827405,0.0004383764,0.9963102,0.00001716865,0.0007320798,0.000007207066],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9943375,0.00134094,0.002444862,0.00006559058,0.00008584797,0.00004136071,0.0002938144,0.00003406372,0.001356043],"genre_scores_gemma":[0.9939937,0.0007605015,0.002848494,0.00004588337,0.00001806353,0.00003372513,0.0004048161,0.00001444024,0.001880347],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001577008,"threshold_uncertainty_score":0.004279971,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0072133437020483,"score_gpt":0.2078605788842156,"score_spread":0.2006472351821673,"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."}}