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Record W1931118628 · doi:10.1029/2005wr004718

General analytical treatment of the flow field relevant to the interpretation of passive fluxmeter measurements

2007· article· en· W1931118628 on OpenAlexaff
Harald Klammler, Kirk Hatfield, Michael D. Annable, Eugene Ofori Agyei, Beth L. Parker, John A. Cherry, P. Suresh C. Rao

Bibliographic record

VenueWater Resources Research · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicGroundwater flow and contamination studies
Canadian institutionsUniversity of Waterloo
FundersEnvironmental Security Technology Certification ProgramU.S. Department of Defense
KeywordsAquiferFlow (mathematics)Sensitivity (control systems)MechanicsInverseConvergence (economics)GeologyStreamlines, streaklines, and pathlinesField (mathematics)GroundwaterSoil scienceGeotechnical engineeringHydrology (agriculture)MathematicsGeometryPhysicsEngineering

Abstract

fetched live from OpenAlex

Relevant flow dynamics for the interpretation of passive fluxmeter (PFM) measurements are investigated by determining the properties of the flow field inside the PFM and its relationship to the undisturbed ambient fluxes in the aquifer. The flow domain is treated in two dimensions and consists of a system of concentric annular filter zones of different radii and hydraulic conductivities. Flow inside the PFM is shown to be uniform regardless of well configuration. Analytical expressions quantifying flow convergence are derived for an increasing number of rings, validated against numerical modeling and used to perform a sensitivity analysis. One of the derived convergence relationships is embedded in an inverse model to estimate aquifer and well screen conductivities and ambient groundwater and methyl‐tertiary‐butyl‐ether (MTBE) fluxes in the Borden Aquifer under controlled flow conditions. Results compare well to independent estimates when the method of quantifying convergence is consistent with field conditions.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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: Methods · Consensus signal: Methods
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.057
GPT teacher head0.328
Teacher spread0.271 · 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 designSimulation or modeling
Domainnot available
GenreMethods

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

Citations24
Published2007
Admission routes1
Has abstractyes

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