{"id":"W4392914703","doi":"10.1016/j.jwpe.2024.105114","title":"Thermal hydrolysis pretreatment of wastewater biosolids: Modelling the impact of the aerobic sludge age","year":2024,"lang":"en","type":"article","venue":"Journal of Water Process Engineering","topic":"Anaerobic Digestion and Biogas Production","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University; Western University","funders":"Natural Sciences and Engineering Research Council of Canada; Trane Technologies","keywords":"Biosolids; Wastewater; Hydrolysis; Pulp and paper industry; Chemistry; Thermal hydrolysis; Sewage sludge; Sewage treatment; Aerobic digestion; Environmental science; Waste management; Sewage sludge treatment; Activated sludge; Environmental engineering; Biochemistry; Engineering","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":[0.0003707597,0.0006914842,0.0009357433,0.0003668944,0.0004246763,0.001252044,0.0006348623,0.001900959,0.002058646],"category_scores_gemma":[0.0007973805,0.000482989,0.0009940772,0.0004369246,0.0005105793,0.0007994248,0.0003481503,0.0007655958,0.0002568332],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001175365,"about_ca_system_score_gemma":0.001102346,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03779899,"about_ca_topic_score_gemma":0.01785375,"domain_scores_codex":[0.9998791,0.00002326122,0.000007987509,0.000022228,0.00001811883,0.00004922226],"domain_scores_gemma":[0.9995589,0.0003018619,0.00003536699,0.00002241623,0.00005104896,0.00003050805],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002299395,0.0001346804,0.001251986,0.00006148488,0.00002281028,0.00006662648,0.00002332526,0.987288,0.008380529,0.0004170304,0.0000770209,0.002046553],"study_design_scores_gemma":[0.00002668036,0.0001146365,0.001155646,0.000004389442,0.0000173107,0.000007993954,0.00002633122,0.9945191,0.003811404,0.000166238,0.0001404239,0.000009861091],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.992592,0.0002423928,0.002998811,0.00009562436,0.00002318229,0.00002843565,0.0002049164,0.00002757824,0.003787158],"genre_scores_gemma":[0.9976847,0.0001637208,0.0005517606,0.00001021751,0.000004318499,0.00001591648,0.00007400676,0.000008222236,0.001487258],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03779899,"threshold_uncertainty_score":0.075158,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008726302328532129,"score_gpt":0.2123577077300156,"score_spread":0.2036314054014834,"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."}}