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Record W1964441459 · doi:10.1061/9780784412312.099

Conceptual Water Sharing Plan for Tarrant Regional Water District (TRWD) and the City of Dallas, TX

2012· article· en· W1964441459 on OpenAlexaff
Kirk Westphal, Lisa M. Stahr, Dan Buhman, Spandana Tummuri

Bibliographic record

VenueWorld Environmental And Water Resources Congress 2012 · 2012
Typearticle
Languageen
FieldEngineering
TopicWater Systems and Optimization
Canadian institutionsCambridge Memorial Hospital
Fundersnot available
KeywordsPipeline transportWater supplyVariety (cybernetics)Pipeline (software)Plan (archaeology)Capital (architecture)Reliability (semiconductor)Cost sharingBusinessEnvironmental economicsEnvironmental planningComputer scienceEngineeringEnvironmental scienceEnvironmental engineeringEconomicsGeography

Abstract

fetched live from OpenAlex

In North Texas, the Tarrant Regional Water District (TRWD) and the City of Dallas both require major new pipelines to bring water from East Texas. Agreements have been reached to share new conveyance infrastructure, which will be jointly funded and used to save hundreds of millions of dollars in capital costs when compared to building independent pipelines. A shared pipeline will also link the two agencies' water supply reservoir systems, creating the potential to share water supply. Preliminary assessments of water sharing suggested there may be beneficial opportunities to either improve supply reliability or reduce operating costs under certain conditions. The analysis focused on a variety of ways that each supplier could share supply with the other. Rules and operational strategies were tested with an integrated operations model. The most promising concepts were refined, rules were developed to initiate and terminate water sharing, and these results were used to suggest an operational strategy for this type of water sharing.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.128
Threshold uncertainty score0.255

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 studies0.0020.001
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0130.001

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 head0.014
GPT teacher head0.171
Teacher spread0.157 · 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 designTheoretical or conceptual
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
Published2012
Admission routes1
Has abstractyes

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