{"id":"W2990434985","doi":"10.1016/j.watres.2019.115328","title":"A microsieve-based filtration process for combined sewer overflow treatment with nutrient control: Modeling and experimental studies","year":2019,"lang":"en","type":"article","venue":"Water Research","topic":"Urban Stormwater Management Solutions","field":"Environmental Science","cited_by":20,"is_retracted":false,"has_abstract":false,"ca_institutions":"Trojan Technologies (Canada); Western University","funders":"Mitacs","keywords":"Turbidity; Chemical oxygen demand; Filtration (mathematics); Zeolite; Combined sewer; Suspended solids; Powdered activated carbon treatment; Activated carbon; Total suspended solids; Water treatment; Chemistry; Phosphorus; Environmental engineering; Pulp and paper industry; Environmental science; Sewage treatment; Wastewater; Stormwater; Adsorption; Organic chemistry; Mathematics; Engineering; Catalysis; Ecology","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":[0.0003512194,0.0004215693,0.0008843442,0.0003425966,0.0007522054,0.000898875,0.0005445207,0.0007377266,0.001043273],"category_scores_gemma":[0.0004521829,0.0002063113,0.0005532212,0.0003603385,0.0003714676,0.0006448037,0.0003170272,0.0004591107,0.0001345207],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009521872,"about_ca_system_score_gemma":0.0009408645,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01525403,"about_ca_topic_score_gemma":0.0136891,"domain_scores_codex":[0.9998011,0.00002329346,0.00001276625,0.0000515312,0.00006986941,0.00004146738],"domain_scores_gemma":[0.9997467,0.00009076374,0.00003898001,0.00001652045,0.00007436134,0.00003257753],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002376654,0.003348484,0.008802532,0.0004423596,0.00007639068,0.0001976754,0.00024965,0.08294757,0.863997,0.0007352792,0.0003475266,0.03647891],"study_design_scores_gemma":[0.0001675071,0.004368765,0.0109401,0.00001929822,0.0001190611,0.00006156221,0.0001671567,0.3289391,0.6539387,0.0001831281,0.001044553,0.00005116714],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9956721,0.0001148307,0.003726993,0.00002294358,0.00001280164,0.00002855664,0.00004318817,0.00004037314,0.0003382259],"genre_scores_gemma":[0.9963731,0.0001906133,0.002620297,0.000007753498,0.000003278373,0.00002388455,0.00003240408,0.000004877774,0.0007439455],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01525403,"threshold_uncertainty_score":0.03033048,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0731699511527563,"score_gpt":0.3412135886549665,"score_spread":0.2680436375022102,"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."}}