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Record W4391367727 · doi:10.2175/193864718825159146

Designing and Integrating Toronto's Largest Sanitary/Combined Sewer Overflow Pumping Station

2023· article· en· W4391367727 on OpenAlexaboutno aff
Pat Schlotzhauer, Nancy Afonso

Bibliographic record

VenueProceedings of the Water Environment Federation · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Stormwater Management Solutions
Canadian institutionsnot available
Fundersnot available
KeywordsSanitary sewerCombined sewerEnvironmental scienceComputer scienceCivil engineeringTransport engineeringMarine engineeringEngineeringHydrology (agriculture)Environmental engineeringGeotechnical engineeringStormwater

Abstract

fetched live from OpenAlex

Designing and Integrating Toronto's Largest Sanitary/Combined Sewer Overflow Pumping StationAbstractThe City of Toronto has launched the largest and most significant stormwater management program in its history to prevent combined sewer overflows (CSO) from entering the waterways. The program includes over 30 km of new tunnels and storage shafts, a new pumping station, a Landform Project with a High-Rate Treatment Facility, and a new treatment plant outfall to Lake Ontario. The new Integrated Pumping Station (IPS) will replace two aging sanitary pumping stations and add a Wet Weather Flow (WWF) pumping system to pump Combined Sewer Overflows (CSOs) to a new high-rate treatment facility. The program will greatly improve the water quality in the Lower Don River, Taylor-Massey Creek and along Toronto’s Inner Harbour by treating CSOs and keeping them out of the waterways. This paper will focus on the design aspects of the new Integrated Pumping Station, highlighting some of the key construction considerations necessary to maintain plant operations throughout construction.The City of Toronto has launched the largest and most significant stormwater management program in its history to prevent combined sewer overflows from entering its waterways. A new Integrated Pumping Station (IPS) will replace two aging sanitary pumping stations and add a wet weather pumping system to pump combined sewer to a new high-rate treatment facility. The program will greatly improve the water quality in the Lower Don River, Taylor-Massey Creek, and keeping them out of the waterways.SpeakerSchlotzhauer, PatPresentation time09:30:0009:50:00Session time08:30:0010:00:00SessionDesign and Construction Challenges for CSO Control ImplementatioinSession locationRoom S403a - Level 4TopicCollection Systems, Intermediate Level, Wet WeatherTopicCollection Systems, Intermediate Level, Wet WeatherAuthor(s)Schlotzhauer, PatAuthor(s)P. Schlotzhauer 1; N. Afonso 2 ; W. Wilton Scott 3; P. Schlotzhauer 1;Author affiliation(s)Black & Veatch 1; City of Toronto 2 ; City of Toronto 3; Black & Veatch 1;SourceProceedings of the Water Environment FederationDocument typeConference PaperPublisherWater Environment FederationPrint publication date Oct 2023DOI10.2175/193864718825159146Volume / Issue Content sourceWEFTECCopyright2023Word count11

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.596
Threshold uncertainty score0.804

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.002

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 head0.009
GPT teacher head0.190
Teacher spread0.180 · 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 designNot applicable
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
Published2023
Admission routes1
Has abstractyes

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