{"id":"W7132990155","doi":"","title":"Linear System Identification of an Urban Drainage System with the Integrator-Delay-Zero Model","year":2024,"lang":"","type":"dissertation","venue":"TSpace","topic":"Hydraulic flow and structures","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Connaught Fund; University of Toronto","keywords":"Electrical conduit; Flooding (psychology); Identification (biology); Drainage; Drainage system (geomorphology); Drainage network; System identification; Controller (irrigation); Stormwater","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005737774,0.0008301607,0.0008714409,0.0003223263,0.0002786271,0.0002736246,0.0007479902,0.0006382669,0.00001112657],"category_scores_gemma":[0.00002720413,0.0005730567,0.00025664,0.0006826805,0.00009370235,0.0002108855,0.00003517825,0.001156634,0.00007940717],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004405783,"about_ca_system_score_gemma":0.0002163919,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004067812,"about_ca_topic_score_gemma":0.000225639,"domain_scores_codex":[0.9968293,0.0001878574,0.0009824365,0.0007634274,0.0007579392,0.0004789904],"domain_scores_gemma":[0.9977372,0.000088423,0.0004666856,0.001171749,0.0003558573,0.0001801234],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001658467,0.00002358883,0.000003989414,0.02021826,0.0006095486,0.00005200356,0.08517946,0.8076228,0.01739998,0.0678876,0.0004946609,0.0003422107],"study_design_scores_gemma":[0.0002336858,0.000121141,0.00002327604,0.002346004,0.0006585118,0.00004222562,0.05869648,0.929449,0.007681377,0.00004631582,0.0001600709,0.0005419381],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8442031,0.003709827,0.1286875,0.0001209609,0.002413605,0.001841094,0.0001155088,0.0009289577,0.01797947],"genre_scores_gemma":[0.9879111,0.00001809128,0.0002858629,0.000004081585,0.0003274123,0.0001540139,0.0004419798,0.0002548049,0.01060266],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.143708,"threshold_uncertainty_score":0.9996721,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00758831248292494,"score_gpt":0.258501420658555,"score_spread":0.2509131081756301,"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."}}