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Record W1550068944 · doi:10.2172/919161

Naval submarine base Kings Bay and Bangor soil evaluations.

2004· report· en· W1550068944 on OpenAlexaff
David J. Holcomb, Raymond Patteson, Donald Wesenberg, S.W. Attaway

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEngineering
TopicGeotechnical and construction materials studies
Canadian institutionsGeomechanica (Canada)
Fundersnot available
KeywordsBaySubmarineEnvironmental scienceSoil waterHydrology (agriculture)GeologyGeotechnical engineeringOceanographySoil science

Abstract

fetched live from OpenAlex

This report provides soil evaluation and characterization testing for the submarine bases at Kings Bay, Georgia, and Bangor, Washington, using triaxial testing at high confining pressures with different moisture contents. In general, the samples from the Bangor and Kings Bay sites appeared to be stronger than a previously used reference soil. Assuming the samples of the material were representative of the material found at the sites, they should be adequate for use in the planned construction. Since soils can vary greatly over even a small site, a soil specification for the construction contractor would be needed to insure that soil variations found at the site would meet or exceed the requirements. A suggested specification for the Bangor and Kings Bay soils was presented based on information gathered from references plus data obtained from this study, which could be used as a basis for design by the construction contractor.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.082
Threshold uncertainty score0.163

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.021
GPT teacher head0.251
Teacher spread0.229 · 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
Published2004
Admission routes1
Has abstractyes

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