{"id":"W3023160309","doi":"10.3390/su12093731","title":"Bacterial Augmented Floating Treatment Wetlands for Efficient Treatment of Synthetic Textile Dye Wastewater","year":2020,"lang":"en","type":"article","venue":"Sustainability","topic":"Constructed Wetlands for Wastewater Treatment","field":"Environmental Science","cited_by":60,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Government College University, Lahore; Higher Education Commission, Pakistan; King Saud University","keywords":"Wastewater; Effluent; Chemical oxygen demand; Phragmites; Total suspended solids; Biochemical oxygen demand; Constructed wetland; Chemistry; Pollutant; Sewage treatment; Bioremediation; Pulp and paper industry; Environmental remediation; Environmental chemistry; Biodegradation; Environmental engineering; Wetland; Environmental science; Contamination; Biology; Ecology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.00007719975,0.0003462906,0.000270739,0.0001550807,0.0001153673,0.0003206937,0.0002052058,0.000273653,0.0002875159],"category_scores_gemma":[0.00006389997,0.0000989722,0.0003670022,0.0001005455,0.0001107587,0.0002146389,0.0003273623,0.0003442744,0.0000886288],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001752312,"about_ca_system_score_gemma":0.0002070953,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001964659,"about_ca_topic_score_gemma":0.002911114,"domain_scores_codex":[0.9999064,0.0000114141,0.00000521102,0.00001786118,0.00003422622,0.00002479385],"domain_scores_gemma":[0.9999673,0.000003610789,0.000009611845,0.00000236123,0.000007327671,0.000009810072],"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":[0.00003418812,0.00002732838,0.0001371241,0.00004508732,0.000004829315,0.00004380729,0.000008235102,0.0001055859,0.9973018,0.0000255889,0.00001816257,0.002248186],"study_design_scores_gemma":[0.00002317219,0.0006431232,0.004812324,0.000009881863,0.00003422444,0.0001803753,0.000051743,0.003858289,0.9884471,0.00003972763,0.001887821,0.00001213204],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9931851,0.0007911329,0.005204101,0.00005282366,0.00002960371,0.00003530078,0.00007193966,0.00006431825,0.0005656474],"genre_scores_gemma":[0.9922234,0.000617055,0.005888429,0.00002702765,0.00000625756,0.00002385848,0.0000897607,0.000008271079,0.001115874],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001964659,"threshold_uncertainty_score":0.003906488,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01104844273186654,"score_gpt":0.2344351715603706,"score_spread":0.223386728828504,"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."}}