{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001246823,0.0001618874,0.0002184645,0.0002225124,0.0001603844,0.0000196571,0.0001922419,0.0001911192,0.00004000157],"category_scores_gemma":[0.00004191411,0.0001315972,0.00003230973,0.00008774662,0.0001778686,0.00004140405,0.0000909622,0.0001443813,0.00001541752],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005183424,"about_ca_system_score_gemma":0.000005143594,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001760882,"about_ca_topic_score_gemma":0.000009715447,"domain_scores_codex":[0.9992446,0.00001805408,0.0001917601,0.000285208,0.00009082029,0.0001695587],"domain_scores_gemma":[0.99932,0.000009000025,0.00009372582,0.0005176521,0.00002309397,0.00003655962],"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":[0.0002267486,0.00246162,0.06036337,0.00005612426,0.0007678018,0.00005917294,0.0008922797,0.0002390416,0.5639461,0.08634932,0.0005125368,0.2841258],"study_design_scores_gemma":[0.002401848,0.006523579,0.1634369,0.00008005986,0.0001454267,0.00002784547,0.001084223,0.0004070815,0.8148976,0.002908614,0.007457841,0.000629029],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9978777,0.0001782489,0.0002590613,0.0003711004,0.0001342764,0.0003506659,0.000005104224,0.0003065172,0.0005173581],"genre_scores_gemma":[0.9992886,0.0001719999,0.000349791,0.000009956598,0.00002528546,0.00004718693,0.000006324767,0.00001202643,0.0000888654],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2834968,"threshold_uncertainty_score":0.5366377,"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."}}