{"id":"W1970140592","doi":"10.2495/wm060211","title":"Data acquisition, validation and forecasting for a combined sewer network","year":2006,"lang":"en","type":"article","venue":"WIT transactions on ecology and the environment","topic":"Urban Stormwater Management Solutions","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Univariate; Hydrograph; Computer science; Redundancy (engineering); Calibration; Multivariate statistics; Drainage basin; Environmental science; Hydrology (agriculture); Engineering; Statistics; Cartography; Geography","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":[0.001199852,0.000691002,0.0006609278,0.00112645,0.0005189728,0.0007480319,0.0008591682,0.0005830111,0.001964377],"category_scores_gemma":[0.002682373,0.0003785607,0.0003447858,0.0007895401,0.000268794,0.0009678376,0.0005811927,0.000466257,0.0005420837],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006963601,"about_ca_system_score_gemma":0.0009719909,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007701075,"about_ca_topic_score_gemma":0.007354831,"domain_scores_codex":[0.9993656,0.00009617744,0.00005322995,0.0002142303,0.0002352132,0.00003561091],"domain_scores_gemma":[0.9988244,0.000392668,0.0001039334,0.0002702118,0.0003536661,0.00005515189],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.001104257,0.0004538498,0.0594961,0.0002007991,0.00009800286,0.0002432892,0.0002625,0.4399099,0.05615393,0.001529562,0.002819198,0.4377286],"study_design_scores_gemma":[0.00004960629,0.0001359687,0.008895996,0.00001190855,0.00002154218,0.00004266984,0.00002593015,0.96907,0.01940108,0.0004116654,0.001910816,0.00002282014],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3675208,0.00007816574,0.6180602,0.000120798,0.00005272822,0.0003443185,0.002518365,0.008764377,0.002540225],"genre_scores_gemma":[0.7509866,0.00006836727,0.243963,0.00002355764,0.00001469943,0.0004970788,0.002614124,0.0001448951,0.001687654],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007701075,"threshold_uncertainty_score":0.01531249,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01763509731302448,"score_gpt":0.192750037497762,"score_spread":0.1751149401847376,"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."}}