{"id":"W1966171481","doi":"10.2166/wst.2009.101","title":"Hydraulic fractionation of conventional water quality constituents in municipal dry- and wet-weather flow samples","year":2009,"lang":"en","type":"article","venue":"Water Science & Technology","topic":"Urban Stormwater Management Solutions","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Combined sewer; Settling; Elutriation; Environmental science; Sewage; Water quality; Environmental engineering; Hydrology (agriculture); Sewage treatment; Stormwater; Engineering; Geotechnical engineering; Chemistry; Ecology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0002612065,0.0001679116,0.0001584577,0.0009367106,0.000677414,0.000426152,0.0001539641,0.0002170958,0.00118731],"category_scores_gemma":[0.0004314324,0.0000851117,0.0001248016,0.001046937,0.0003366462,0.000205464,0.0001719035,0.0002715763,0.0002115384],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004993025,"about_ca_system_score_gemma":0.00055254,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02252341,"about_ca_topic_score_gemma":0.03021706,"domain_scores_codex":[0.9997984,0.00001839557,0.00001494927,0.00004012106,0.00007459681,0.00005358163],"domain_scores_gemma":[0.9998287,0.00002864546,0.00002292141,0.000009912283,0.0000896302,0.00002020351],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0003083122,0.0000854593,0.01854899,0.00007765738,0.00001277978,0.0000709915,0.0004105616,0.0003822259,0.9689806,0.000245723,0.0001690559,0.01070767],"study_design_scores_gemma":[0.00002117461,0.0004055431,0.1627702,0.00001668403,0.00004320769,0.0001746917,0.001042878,0.002824357,0.8281875,0.000184122,0.004306877,0.00002269564],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.994238,0.0001469498,0.002653767,0.00002491,0.000008727629,0.00006508511,0.0005016985,0.0000613701,0.002299509],"genre_scores_gemma":[0.9917378,0.0002238994,0.003949228,0.00006971972,0.000007540609,0.00008274953,0.001377327,0.00002683928,0.002524799],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02252341,"threshold_uncertainty_score":0.04478461,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01973238864364667,"score_gpt":0.2628549559269927,"score_spread":0.243122567283346,"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."}}