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Record W2462721263 · doi:10.1520/gtj20150118

Assessment of the WP4-T Device for Measuring Total Suction

2016· article· en· W2462721263 on OpenAlexaff
N. Ebrahimi-Birang, D. G. Fredlund

Bibliographic record

VenueGeotechnical Testing Journal · 2016
Typearticle
Languageen
FieldEngineering
TopicSoil and Unsaturated Flow
Canadian institutionsGolder Associates (Canada)SNC-Lavalin (Canada)
Fundersnot available
KeywordsSuctionSiltGeotechnical engineeringMaterials scienceSoil waterRange (aeronautics)HysteresisDesorptionDew pointSoil scienceEnvironmental scienceMechanicsComposite materialAdsorptionGeologyThermodynamicsChemistryPhysics

Abstract

fetched live from OpenAlex

Abstract Soil-water characteristic curves (SWCCs) play a key role in the determination of unsaturated soil property functions for use with predictive numerical models. Most studies on the soil-water characteristic curve have been limited to the desorption branch in the low suction range (i.e., less than 1500 kPa). There is limited measured data on desorption and adsorption branches (i.e., hysteresis effects) in the high suction range. The dew-point Water PotentiaMeter (i.e., WP4-T) is a device that has been introduced into the commercial market for measuring total suction in the high suction range. The WP4-T device can reduce the time and costs associated with suction measurements in the high suction range. The performance of the WP4-T was evaluated using experimental data measured on Regina clay and Botkin silt soils. Measurements of total suction using the WP4-T device were compared with vacuum desiccator results using a range of saturated salt solutions. The results showed that the WP4-T device provides excellent results in the high suction range branches of the SWCC.

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)0.000
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 score0.488
Threshold uncertainty score0.194

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.041
GPT teacher head0.255
Teacher spread0.215 · 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

Citations12
Published2016
Admission routes1
Has abstractyes

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