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Record W816960191 · doi:10.1520/gtj20130175

Parasitic Head Losses During Laboratory Permeability Tests

2015· article· en· W816960191 on OpenAlex
François Duhaime, Robert P. Chapuis, Simon Weber

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueGeotechnical Testing Journal · 2015
Typearticle
Languageen
FieldEngineering
TopicSoil and Unsaturated Flow
Canadian institutionsPolytechnique MontréalÉcole de Technologie Supérieure
Fundersnot available
KeywordsPermeameterBlankHydraulic headHead (geology)Geotechnical engineeringPermeability (electromagnetism)Soil testHydraulic conductivityLaboratory testGeologyMaterials scienceEnvironmental scienceEngineeringComposite materialSoil scienceSoil waterChemistry

Abstract

fetched live from OpenAlex

Abstract Parasitic head losses incurred outside the tested soil specimen may alter the results of laboratory permeability tests. They can be measured by running a blank test in an empty permeameter, and determining the flow resistance of the testing equipment. They can also be assessed by using the difference between a constant-head test, where the hydraulic heads are measured within the tested specimen, and a variable-head test, where the hydraulic heads are measured outside the specimen and include the parasitic head losses of the testing equipment. When not accounted for, they can lead to permeability values that are underestimated. An electric analog provides an analytical relationship between variable- and constant-head test results. The parameters in the analytical solution can be obtained via blank permeability tests. This article emphasizes the need to measure hydraulic heads inside the soil specimen during laboratory permeability tests.

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.

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)0.003
Version: codex-gemma-dda1882f352aValidation 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 score0.636
Threshold uncertainty score0.742

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
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 head0.041
GPT teacher head0.269
Teacher spread0.228 · 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