{"id":"W1979181822","doi":"10.1016/j.biortech.2010.04.021","title":"Alkaline extraction of wastewater activated sludge biosolids","year":2010,"lang":"en","type":"article","venue":"Bioresource Technology","topic":"Wastewater Treatment and Nitrogen Removal","field":"Environmental Science","cited_by":71,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"Ontario Ministry of Research and Innovation; Consejo Nacional de Ciencia y Tecnología","keywords":"Extraction (chemistry); Chemistry; Activated sludge; Organic matter; Biosolids; Wastewater; Lysis; Chromatography; Fraction (chemistry); Organic chemistry; Waste management; Biochemistry","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00008492795,0.0001540119,0.0001676275,0.0001652252,0.00006469725,0.000006884511,0.0002749084,0.0003023786,0.001796462],"category_scores_gemma":[0.00001849318,0.000120317,0.00005898801,0.0004018427,0.0004414187,0.0000761319,0.0001822269,0.0002301853,0.0005621886],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002907683,"about_ca_system_score_gemma":0.000004121796,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001145581,"about_ca_topic_score_gemma":0.00005170329,"domain_scores_codex":[0.9990804,0.00001547938,0.0002020678,0.0002745162,0.0001466881,0.0002808151],"domain_scores_gemma":[0.9994177,0.00001379877,0.0001027578,0.0004034475,0.000008386465,0.00005388071],"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":[0.00003115075,0.0001214078,0.01739697,0.000002322636,0.00001601729,0.00001092335,0.00004612735,0.000002957957,0.9793333,0.00008425888,0.0003596123,0.002594931],"study_design_scores_gemma":[0.0003598896,0.0001178426,0.00339733,0.000003066908,0.00001811472,0.00007590848,0.00006149216,0.00003451537,0.9621558,0.0003280599,0.03332486,0.0001231239],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977593,0.000009219414,0.00001360032,0.0006031976,0.0001191002,0.0001473586,0.000006182079,0.0002061609,0.001135892],"genre_scores_gemma":[0.9928803,0.000002710089,0.006184554,0.00002067863,0.00003252868,0.00001169315,0.0000115351,0.00001835906,0.0008376609],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03296524,"threshold_uncertainty_score":0.999116,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007501506093312658,"score_gpt":0.2268996697592887,"score_spread":0.2193981636659761,"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."}}