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Record W2319531305 · doi:10.1061/9780784479360.043

Fast Track Relief to Midland’s Emergency Thirst

2015· article· en· W2319531305 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 2015 · 2015
Typearticle
Languageen
FieldDecision Sciences
TopicConstruction Project Management and Performance
Canadian institutionsSmiths Detection (Canada)
Fundersnot available
KeywordsScheduleTrack (disk drive)Project managementIntegrated project deliveryComputer scienceDelivery systemEngineering managementTransport engineeringOperations managementEngineeringSystems engineeringOperating system

Abstract

fetched live from OpenAlex

Using the traditional design-bid-build (DBB) project delivery system, the T-Bar Ranch Well Field Development & Delivery System project would likely have taken upwards of three or four years to complete. With the City of Midland, Texas, deep in a severe drought, an alternative delivery system was a necessity. The City was facing the probability of being cut off from their primary source of water in less than fifteen (15) months. By means of the design-build (DB) delivery system — in this case, design-build-finance-operate (DBFO) — the Project Team took tasks that, using the DBB system would have been completed in a linear manner, and overlapped them, tackling them in conjunction with one another, significantly decreasing the overall project schedule and ultimately the cost to build. Diligent management of the land acquisition, design, material manufacturing, and construction resources delivered this project ahead of schedule and under budget.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.238
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.013

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 head0.177
GPT teacher head0.418
Teacher spread0.242 · 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