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Some Uncertainties in Embankment Dam Engineering

2003· article· en· W2050022583 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

VenueJournal of Geotechnical and Geoenvironmental Engineering · 2003
Typearticle
Languageen
FieldEngineering
TopicDam Engineering and Safety
Canadian institutionsGolder Associates (Canada)
Fundersnot available
KeywordsLeveeEmbankment damGeotechnical engineeringGeologyCivil engineeringCurrent (fluid)Engineering

Abstract

fetched live from OpenAlex

In the design and construction of embankment dams, our current capability for precise mathematical analysis and modeling of induced stresses and deformations, or of potential seepage patterns, far exceeds our capability to make judgments of comparable accuracy concerning, for example, the site and geology or how the soil properties may be affected by the weather or by the contractor’s methods. In addition, there is often a lack of adequate communication between the design and the supervision of construction. These uncertainties or doubts about the actual performance of the dam when constructed are discussed in the paper and illustrated by case history examples, with particular reference to the uncertain effects of cold weather, to the use of broadly graded soils (tills) as core and to problems in the placement, and segregation of tills and filter materials.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.108
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.001
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 head0.003
GPT teacher head0.160
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