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Record W4402059365 · doi:10.1061/9780784485569.004

Buffalo Pound Non-Potable Water Supply System Regina Regional Pipeline

2024· article· en· W4402059365 on OpenAlexaff
Keith Kingsbury, Chris Robart, Darin Schindel, Kristin Sies

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicDiverse Research and Applications
Canadian institutionsStillwater (Canada)
Fundersnot available
KeywordsPound (networking)Pipeline (software)Potable waterWater supplyEnvironmental sciencePipeline transportComputer scienceWater resource managementEnvironmental engineeringOperating systemWorld Wide Web

Abstract

fetched live from OpenAlex

The Buffalo Pound Non-Potable Water Supply System (BPNPWSS)–Regina Regional will supply non-potable water from Buffalo Pound Lake to industrial customers around Regina. The Regina Regional System is an extension of the existing BPNPWSS–East that currently supplies non-potable water to industrial customers in the Belle Plaine corridor. The planning of the pipeline began with utilizing GIS to show existing constraints. Once the route was chosen, hydraulic analysis was completed to determine the required pressure rating and diameter of the pipe to deliver the required water to the end users. The design of the pipeline took a unique and alternative delivery approach. The design of the pipeline was completed to 80% without a specified pipe type for procurement. A Request for Supplier Qualifications (RFSQ) pre-qualified three contractors to submit a proposal to complete the work. The proposals included the contractor’s proposed pipeline material for each section meeting the specified criteria, work plan and schedule, additional details on their previous experience, and their proposal price. Once the pipe types were chosen, the design was completed with the selected contractor’s input and construction began in May 2023. This paper will provide an overview of the planning and design process determining the pipeline route utilizing GIS, to 80% design of the pipeline, and finally to obtaining a qualified contractor and completing the design and construction. We will also discuss the challenges and benefits that this approach brought on.

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: none
Teacher disagreement score0.057
Threshold uncertainty score0.139

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0420.010

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 head0.260
Teacher spread0.239 · 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
Published2024
Admission routes1
Has abstractyes

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Same topicDiverse Research and ApplicationsFrench-language works237,207