{"id":"W4386256502","doi":"10.3390/bioengineering10091017","title":"Waste Activated Sludge-High Rate (WASHR) Treatment Process: A Novel, Economically Viable, and Environmentally Sustainable Method to Co-Treat High-Strength Wastewaters at Municipal Wastewater Treatment Plants","year":2023,"lang":"en","type":"article","venue":"Bioengineering","topic":"Wastewater Treatment and Nitrogen Removal","field":"Environmental Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Activated sludge; Waste management; Wastewater; Sewage treatment; Process (computing); Environmental science; Environmentally friendly; Engineering; Computer science; Ecology; Biology","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002292226,0.0008828181,0.0006932638,0.0002874667,0.0003703749,0.0001449754,0.000304668,0.0001805451,0.0004675599],"category_scores_gemma":[0.000006438117,0.0006901247,0.0001411461,0.0003391276,0.0001038587,0.0004190428,0.0004203279,0.00009581375,0.0008176932],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002369705,"about_ca_system_score_gemma":0.00002129175,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001684998,"about_ca_topic_score_gemma":0.00008941895,"domain_scores_codex":[0.996502,0.00008148735,0.000508597,0.001158917,0.0002858475,0.001463136],"domain_scores_gemma":[0.9985992,0.0001106055,0.0001114419,0.0005712356,0.000006287944,0.0006012467],"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":[0.0004873828,0.0003495027,0.001918357,0.00004903839,0.0003603409,0.0002826485,0.002200786,0.09199283,0.901151,0.00001361912,0.000139593,0.001054927],"study_design_scores_gemma":[0.003815002,0.001315058,0.001971425,0.00003830168,0.0001480201,0.00006732801,0.001473393,0.006295851,0.9773505,0.00001765425,0.006700077,0.0008073827],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975184,0.00003203924,0.00005192279,0.0003098571,0.0001069396,0.001257911,0.0002262169,0.000327005,0.0001696933],"genre_scores_gemma":[0.9784638,0.0001401947,0.007800002,0.00005304093,0.00009027919,0.0004529535,0.0004982824,0.0001495332,0.01235188],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08569697,"threshold_uncertainty_score":0.9999603,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01180120760999138,"score_gpt":0.2304549981624188,"score_spread":0.2186537905524275,"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."}}