MétaCan
Menu
Back to cohort
Record W2119185875 · doi:10.14796/jwmm.r235-11

Storm Drainage System Modeling of Edmonton's Clareview and Pilot Sound Storm Basins

2009· article· en· W2119185875 on OpenAlexvenueaboutno aff
Steven Chan, Michelle Yu, Scott Neuman, Magdy Hashem

Bibliographic record

VenueJournal of Water Management Modeling · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Stormwater Management Solutions
Canadian institutionsnot available
Fundersnot available
KeywordsStormSound (geography)DrainageHydrology (agriculture)Drainage system (geomorphology)GeologyDrainage basinMeteorologyEnvironmental scienceOceanographyGeographyGeotechnical engineeringCartography

Abstract

fetched live from OpenAlex

The City of Edmonton operates and maintains over 5,000 km of sewer pipes.The collection system is made up of about 42% storm sewers, 39% sanitary sewers and 19% combined sewers.Storm drainage is captured and discharged to the North Saskatchewan River.Flows from the combined sewer area and the sanitary sewerage system are collected and discharged to the Gold Bar Wastewater Treatment Plant.This chapter presents the development and applications of the Clareview and Pilot Sound Storm Drainage Model.The study area is approximately 1350 ha and located on the north east side of the City servicing a population of about 18,000 mainly residential with portions of commercial, community services and industrial.A storm model was developed using DHI's Mike Urban and Mike Flood to represent approximately 69 km of 1,200 pipes and 370 sub-basins within the study boundary.Pipe diameters vary from 200 mm to 2250 mm.The model also includes a pump station, five stormwater detention facilities and a number of flow diversion control structures.The main components of the study include development of model parameters and the drainage network, calibration and verification of the model, assessment of the capacity constraints of the existing system under various storm events, evaluation of the performance of the stormwater detention facilities under severe storm 177

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.499
Threshold uncertainty score0.996

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.030
GPT teacher head0.228
Teacher spread0.198 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2009
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Water Management ModelingSame topicUrban Stormwater Management SolutionsFrench-language works237,207