{"id":"W4318426592","doi":"10.1016/j.jece.2023.109406","title":"Integrated ozonation as a strategy for enhancing treatment of municipal wastewater in facultative sewage lagoons","year":2023,"lang":"en","type":"article","venue":"Journal of environmental chemical engineering","topic":"Pharmaceutical and Antibiotic Environmental Impacts","field":"Environmental Science","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"Trent University; Environment and Climate Change Canada; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Environment and Climate Change Canada; Ontario Ministry of Natural Resources and Forestry","keywords":"Facultative lagoon; Wastewater; Sewage; Facultative; Effluent; Sewage treatment; Environmental science; Environmental chemistry; Environmental engineering; Water quality; Pulp and paper industry; Biology; Ecology; 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":[0.0001486335,0.0001856279,0.0002854122,0.0000849132,0.00001912009,0.000008610557,0.0001294788,0.00007524898,0.0003139697],"category_scores_gemma":[0.00004432113,0.0001479537,0.0001363244,0.0001746233,0.00009132482,0.0002129374,0.0000632624,0.0001313366,0.00004683479],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005205474,"about_ca_system_score_gemma":0.0000057969,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000262057,"about_ca_topic_score_gemma":0.000004141385,"domain_scores_codex":[0.9987858,0.00001666165,0.0004795997,0.0001585046,0.0002542875,0.0003051776],"domain_scores_gemma":[0.9995132,0.0001238983,0.0001336441,0.00007344377,0.000001652312,0.0001541621],"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":[0.00007104321,0.0002777759,0.0008237968,0.00001470047,0.00003061925,0.00002795912,0.0006974259,0.04285083,0.9528101,0.000005963494,0.000009464267,0.002380345],"study_design_scores_gemma":[0.001571957,0.0005357818,0.007399168,0.00007032679,0.00003507992,0.00003478559,0.0007095726,0.01810574,0.9707324,0.00009239524,0.0005297145,0.0001830632],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9993271,0.00004250597,0.0001571856,0.00005255569,0.00004885547,0.000178587,0.00003952791,0.00001110256,0.0001425468],"genre_scores_gemma":[0.99876,0.0001034974,0.0009167101,0.00001426182,0.00002953295,0.000005693629,0.00002264046,0.00002111067,0.0001265487],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02474509,"threshold_uncertainty_score":0.6033378,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02937477404702997,"score_gpt":0.2867176447102445,"score_spread":0.2573428706632145,"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."}}