{"id":"W2748822431","doi":"10.1016/j.biortech.2017.08.064","title":"Biological hydrolysis pretreatment on secondary sludge: Enhancement of anaerobic digestion and mechanism study","year":2017,"lang":"en","type":"article","venue":"Bioresource Technology","topic":"Anaerobic Digestion and Biogas Production","field":"Engineering","cited_by":92,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada; Ontario Centres of Excellence; Ontario Water Consortium; University of Guelph","keywords":"Anaerobic digestion; Hydrolysis; Chemistry; Digestion (alchemy); Thermal hydrolysis; Pulp and paper industry; Anaerobic exercise; Waste management; Sewage sludge treatment; Chromatography; Biochemistry; Methane; Sewage treatment; Biology; Engineering; Organic chemistry","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":[0.0001360142,0.0003705114,0.0003792305,0.0001565395,0.0001740468,0.0002038388,0.0002053287,0.0003098675,0.001055667],"category_scores_gemma":[0.0001160023,0.0001335702,0.0004488839,0.0001755002,0.0002130876,0.0002563034,0.0001328752,0.0003251583,0.0001940121],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002192076,"about_ca_system_score_gemma":0.000317108,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00111274,"about_ca_topic_score_gemma":0.001232796,"domain_scores_codex":[0.999912,0.000009908174,0.00000408727,0.00001442541,0.00002662258,0.00003294285],"domain_scores_gemma":[0.999948,0.00001073748,0.00001174163,0.00000518562,0.00001490878,0.000009329196],"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":[0.0001008416,0.00004828449,0.0001223524,0.00007807455,0.000004764409,0.00003406179,0.00001280691,0.0001577178,0.9974515,0.0001040323,0.00002909592,0.001856593],"study_design_scores_gemma":[0.000007409803,0.0001536908,0.001706542,0.000003192678,0.00001067791,0.00004291438,0.00002129548,0.001036947,0.9965132,0.00004061006,0.0004597589,0.000003828026],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9947109,0.001184832,0.002622603,0.0000853963,0.00003812525,0.00002137277,0.00005630561,0.00002141555,0.001258947],"genre_scores_gemma":[0.9976724,0.0005081744,0.0006557436,0.00001620839,0.000007222427,0.000006064241,0.00003254182,0.000003122863,0.001098615],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00111274,"threshold_uncertainty_score":0.003531516,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01363684310320166,"score_gpt":0.2295157830980409,"score_spread":0.2158789399948393,"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."}}