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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 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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
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 head0.041
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 source (direct Gemma or distilled Codex), not a consensus.

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