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Record W4391358072 · doi:10.1520/gtj20230433

Assessment of the Applicability of a Constant-Head Borehole Permeameter Test to River Levees

2024· article· en· W4391358072 on OpenAlexaboutno aff
Wenyue Zhang, Akihiro Takahashi

Bibliographic record

VenueGeotechnical Testing Journal · 2024
Typearticle
Languageen
FieldEngineering
TopicSoil and Unsaturated Flow
Canadian institutionsnot available
FundersMinistry of Education, Culture, Sports, Science and Technology
KeywordsPermeameterLeveeGeotechnical engineeringBoreholeGeologyHead (geology)Soil scienceGeomorphologySoil waterHydraulic conductivity

Abstract

fetched live from OpenAlex

ABSTRACT The Guelph Permeameter (GP) test, one of the constant-head borehole permeameter tests, is a potential tool for studying the heterogeneous alluvial deposits in the foundation of river levees. However, the applicability in the targeted environment and adequacy of the information obtained by the tests are still unclear. Experiments are conducted in a model ground and in the field to verify the applicability of the GP test concerning underseepage through river levees. Discussions focus on the effects of the groundwater table, seepage behavior during the test, and the representative volume of soil tested. It is noted that for sandy and silty soils, reasonable estimations of the hydraulic conductivity can be made by applying the Reynolds’ solution, but the estimation of the hydraulic conductivity in clayey soil is affected by the macropores in the soil. The GP tests performed in this study have representative volumes on the order of a few to tens of centimeters so that heterogeneity can be investigated at the meter scale. In summary, the GP test is a useful tool for evaluating the underseepage through river levees.

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 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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.506
Threshold uncertainty score0.338

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0000.000
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 head0.027
GPT teacher head0.278
Teacher spread0.251 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations2
Published2024
Admission routes1
Has abstractyes

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