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Record W2471564868 · doi:10.1061/9780784479957.071

Navajo Gallup Water Supply Project Pipeline Design and Construction Evaluation

2016· article· en· W2471564868 on OpenAlexaff
Andrew Robertson

Bibliographic record

VenuePipelines 2016 · 2016
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsGolder Associates (Canada)
Fundersnot available
KeywordsNavajoWater supplyPipeline transportPipeline (software)Gallon (US)Civil engineeringEngineeringWater pipeEnvironmental scienceForensic engineeringEnvironmental planningEnvironmental engineeringWaste management

Abstract

fetched live from OpenAlex

The Navajo Gallup water supply project reach 24.1/25 project will convey water from the San Juan River to four Navajo Nation (Nation) communities in northwest New Mexico. These Native American communities are among the most water-underserved in the United States. The project includes 13.7 miles of 14- and 10-inch pipeline and a pump station with a capacity of 1,500 gallons per minute. The Nation elected to use PVC for the transmission line, and also utilized fused PVC pipe (FPVCP) for the first time. FPVCP was used for joint restraint sections and for sections of the line where pipe joints were undesirable. This included arroyo crossings, locations of potential contamination, and areas of potential down-surge pressures. This paper will discuss the rationale, benefits, costs, and trade-offs of using FPVCP to provide thrust restraint, reduce risk of pipe failure due to soil erosion, and mitigate risk of contamination at pipe joints. Both advantages and disadvantages of FPVCP will be discussed, as well as lessons learned during construction and design aspects that may be improved upon in future designs using FPVCP as part of typical buried PVC pipe systems.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score0.086

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0060.001

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 head0.016
GPT teacher head0.230
Teacher spread0.214 · 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 designObservational
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
Published2016
Admission routes1
Has abstractyes

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