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Record W1651686692 · doi:10.1029/2002wr001904

Optimal replacement of water pipes

2003· article· en· W1651686692 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueWater Resources Research · 2003
Typearticle
Languageen
FieldEngineering
TopicWater Systems and Optimization
Canadian institutionsInstitut National de la Recherche Scientifique
FundersNational Research Council Canada
KeywordsHazardConstant (computer programming)MinificationExponential functionFunction (biology)Probability density functionBasis (linear algebra)MathematicsMathematical optimizationStatisticsComputer scienceMathematical analysisGeometry

Abstract

fetched live from OpenAlex

Pipe breaks are used as indicators of the structural state of pipe network. The approach used considers times to failure between pipe breaks as random variables. Pipe lifespan is divided into two periods, the first one characterized by time‐dependent hazard functions (nonexponential period) and the second one characterized by constant hazard functions (exponential period). Closed‐form expressions have been derived for probability density functions of occurrence of breaks for all break orders as well as expressions for the time evolution of the average number of pipe breaks per unit time. An optimal replacement criterion is defined on a pipe‐to‐pipe basis based on a cost function using conditional probabilities to estimate the expected future costs. Minimization of this cost function leads to a replacement criterion involving hazard functions. When applied to models with constant hazard functions, this criterion identifies a critical pipe break order at which replacement should be made.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.742
Threshold uncertainty score0.520

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.029
GPT teacher head0.268
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