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An Inexpensive Multilevel Array of Sensors for Direct Ground Water Velocity Measurement

2009· article· en· W2138689498 on OpenAlexaboutno aff
J.F. Devlin, G. P. Tsoflias, M. A. McGlashan, P.C. Schillig

Bibliographic record

VenueGroundwater Monitoring & Remediation · 2009
Typearticle
Languageen
FieldEngineering
TopicGeophysical Methods and Applications
Canadian institutionsnot available
FundersNational Science Foundation
KeywordsFence (mathematics)TRACEREnvironmental scienceFlow velocityFlow (mathematics)Materials scienceRemote sensingGeologyEngineeringMechanicsPhysicsStructural engineering

Abstract

fetched live from OpenAlex

Abstract The point velocity probe (PVP) is an instrument capable of measuring ground water velocity in situ at the centimeter scale. It is based on detecting an electrically conductive tracer transported by ground water around the perimeter of the cylindrical probe. PVPs are easily constructed from inexpensive materials and can be deployed as a single sensor or in multilevel arrays. A multilevel array of these instruments, consisting of four PVPs stacked vertically on each of five stands, was installed as a fence within a sheet‐pile alleyway at the Canadian Forces Base Borden test site in Ontario, Canada. The data from the fence revealed notable velocity variations both spatially and temporally. Ground water velocity data of these kinds are likely to be valuable for permeable reactive barrier design and assessment, regulatory compliance assessments, and a variety of research level investigations concerned with local flow phenomena.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.039
GPT teacher head0.278
Teacher spread0.239 · 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

Citations41
Published2009
Admission routes1
Has abstractyes

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