{"id":"W2810298830","doi":"10.2166/wqrj.2018.003","title":"Recovery of particulate matter from a high-rate moving bed biofilm reactor by high-rate dissolved air flotation","year":2018,"lang":"en","type":"article","venue":"Water Quality Research Journal","topic":"Wastewater Treatment and Nitrogen Removal","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Cégep de Saint-Laurent; EnviroSim (Canada); Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Particulates; Effluent; Moving bed biofilm reactor; Wastewater; Dissolved air flotation; Chemistry; Pulp and paper industry; Waste management; Environmental science; Total suspended solids; Sewage treatment; Hydraulic retention time; Environmental engineering; Biofilm; Chemical oxygen demand","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":[0.0003561401,0.0004952637,0.0004491895,0.0002685251,0.0001816466,0.0004418523,0.0003326566,0.0005102878,0.0004041277],"category_scores_gemma":[0.0001721397,0.0001670223,0.0005676589,0.0001993828,0.0001713206,0.0003183454,0.0002499081,0.0005484933,0.0002863975],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002499514,"about_ca_system_score_gemma":0.0002413784,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001557403,"about_ca_topic_score_gemma":0.00168758,"domain_scores_codex":[0.9998218,0.000025639,0.00001396106,0.00003917187,0.00007191205,0.00002754635],"domain_scores_gemma":[0.999912,0.00001698838,0.00002246542,0.00001065276,0.0000180504,0.00001995261],"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":[0.00001860278,0.00002224975,0.00006013692,0.00002082214,0.00000310465,0.00001106803,0.000003799205,0.00008793613,0.9989629,0.000008143235,0.000006342938,0.0007949222],"study_design_scores_gemma":[0.00001212116,0.0002735702,0.001678086,0.000003767015,0.00001320942,0.00003417589,0.000008062359,0.00180221,0.9958712,0.000008233569,0.0002895223,0.000005800613],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9930841,0.0003434178,0.005948528,0.0000375761,0.00002048254,0.00002822036,0.00008475475,0.00008800753,0.0003649366],"genre_scores_gemma":[0.984782,0.0003704154,0.01314684,0.00002698145,0.00001110945,0.00002333398,0.0002381217,0.00003137775,0.001369717],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001557403,"threshold_uncertainty_score":0.0030967,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04393643511960385,"score_gpt":0.3135820921780262,"score_spread":0.2696456570584224,"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."}}