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Record W1987244578 · doi:10.1520/jte11924

Geotechnical Properties of Compressible Materials Used for Induced Trench Construction

2004· article· en· W1987244578 on OpenAlexaff
RP McAffee, AJ Valsangkar

Bibliographic record

VenueJournal of Testing and Evaluation · 2004
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsCompressibilityTrenchGeotechnical engineeringMaterials scienceGeologyShear (geology)Structural engineeringEngineeringComposite materialMechanicsPhysics

Abstract

fetched live from OpenAlex

Abstract Results of a testing program to measure the compressibility and shear strength parameters of compressible fill materials commonly used for induced trench construction are presented. The geotechnical properties of sawdust, wood chips, and hay have been determined. A large-scale consolidometer and direct shear testing apparatus were used to perform the tests. To resolve strain compatibility issues, the mobilized friction angle corresponding to an appropriate shear displacement value is reported. The experimental results are compared to geotechnical properties of several other compressible materials reported in the literature that also have been used in induced trench applications. The results presented in this paper can be used to perform numerical modeling of induced trenches where these compressible materials are commonly used.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.066
GPT teacher head0.273
Teacher spread0.208 · 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

Citations40
Published2004
Admission routes1
Has abstractyes

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