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Record W2904126871 · doi:10.1520/gtj20170417

Field Permeability Tests with Inward and Outward Flow in Confined Aquifers

2018· article· en· W2904126871 on OpenAlexaff
Lu Zhang, Robert P. Chapuis, Vahid Marefat

Bibliographic record

VenueGeotechnical Testing Journal · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicGroundwater flow and contamination studies
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsAquiferCloggingPermeability (electromagnetism)Internal erosionGeotechnical engineeringHydraulic headGeologyAquifer propertiesAquifer testWater wellFlow (mathematics)RADIUSHead (geology)MechanicsGroundwaterGeomorphologyChemistry

Abstract

fetched live from OpenAlex

Abstract Field permeability tests gave the local hydraulic conductivities (K) at three different sites. Constant head (CH) and variable head (VH) tests were performed using 33 monitoring wells (MWs) installed in confined aquifers. Each test method was conducted with either an inward flow from aquifer to pipe or outward flow from pipe to aquifer, which makes a total of four types of tests: discharge and injection tests (CH) and rising and falling head tests (VH). The MWs were developed soon after their installation to remove the fine particles that were close to the screen areas. This article first explains various test results at different sites. For MWs in perfect condition, two opposite flows should yield equivalent K values. However, the tests with inward flow and outward flow gave different K values, which is due to some clogging of the screen or internal erosion of the filter pack. In addition, the K (CH tests), which are frequently lower than the K (VH tests), are more accurate because the CH test lasts longer and has a larger influence radius. The article also provides recommendations for estimating reliable K values for a confined aquifer.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.189
Threshold uncertainty score0.336

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.021
GPT teacher head0.248
Teacher spread0.226 · 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 designObservational
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

Citations9
Published2018
Admission routes1
Has abstractyes

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