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Record W3187431020 · doi:10.1061/9780784483619.026

New Bonnybrook Wastewater Treatment Plant Treated Effluent Outfall—Design, Contracting, and Construction Overview

2021· article· en· W3187431020 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePipelines 2021 · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsStantec (Canada)
Fundersnot available
KeywordsOutfallEffluentDiffuser (optics)Flood mythEnvironmental scienceWastewaterEnvironmental engineeringSewage treatmentHydrology (agriculture)EngineeringWater resource managementGeographyGeotechnical engineering

Abstract

fetched live from OpenAlex

The Bonnybrook Wastewater Treatment Plant (BBWWTP) is one of the largest cold weather BNR plants in the world undergoing a significant expansion, including a new outfall to discharge all treated effluent into the Bow River. The BBWWTP currently discharges all the treated effluent flow into the Bow River via a conventional bank outfall. The new outfall is not only required for plant expansion but also is an integral part of a flood protection plan for the site. Design of the outfall system was focused to strike a balance between flood protection capabilities, upsize for expected flow increase to year 2076, environmental enhancement, and cost. The outfall is designed to convey 1,962 MLD (22.71 m3/s) (518 MGD) to a new exfiltration style diffuser under the bed of the Bow River. Construction of the new outfall is ongoing and scheduled to be complete by the end of 2021. The presentation will discuss the project drivers and motivations, some of the key design and construction challenges, and contracting strategy used to deliver this infrastructure.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.529
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.000

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 head0.021
GPT teacher head0.237
Teacher spread0.216 · 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