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Record W1997288062 · doi:10.14295/ras.v23i1.17004

ANÁLISE DO MÉTODO DO PERMEÂMETRO DE GUELPH NA DETERMINAÇÃO DA CONDUTIVIDADE HIDRÁULICA SATURADA

2009· article· pt· W1997288062 on OpenAlexaboutno aff
Miguel Alfaro Soto, Kiang Hung Chang, Orêncio Monje Vilar

Bibliographic record

VenueÁguas Subterrâneas · 2009
Typearticle
Languagept
FieldEngineering
TopicSoil and Unsaturated Flow
Canadian institutionsnot available
Fundersnot available
KeywordsPermeameterHydraulic conductivityLoamIsotropyStage (stratigraphy)Soil waterMathematicsSoil scienceGeologyPhysicsOptics

Abstract

fetched live from OpenAlex

The use of the method of the Guelph permeameter has, in many situations, shown to provide unrealistic results such as negative values of the hydraulic conductivity. Although this is attributed essentially to soil heterogeneity, other factors inherent to the test method itself can also interfere with the results. The primary objective of the present work is to analyze the performance and the variability of the Guelph permeameter in determining the hydraulic conductivity of sandy soils and other loamy soils when the one-stage or two-stage load method is employed. Inherent difficulties in meeting with the Kfs condition of isotropy in the two-stage load method are evidenced. Notwithstanding, the use of the two-stage load method is still possible when operational errors are minimized. In compensation, the one-stage method is employed in determining only the saturated hydraulic conductivity (Kfs) and only a reduced number of tests is needed. However, the appropriate choice of the parameter a and the height (H) can minimize the erros associated to estimating Kfs.

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)0.003
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 score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
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 head0.021
GPT teacher head0.251
Teacher spread0.230 · 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

Citations4
Published2009
Admission routes1
Has abstractyes

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