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Record W2011552415 · doi:10.1063/1.2782710

A laboratory apparatus for streaming potential and resistivity measurements on soil samples

2007· article· en· W2011552415 on OpenAlexafffund
M. R. Sheffer, P. M. Reppert, John A. Howie

Bibliographic record

VenueReview of Scientific Instruments · 2007
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeophysical and Geoelectrical Methods
Canadian institutionsUniversity of British Columbia
FundersCanadian Electricity Association
KeywordsStreaming currentElectrical resistivity and conductivityMaterials scienceFlow (mathematics)Coupling (piping)Soil testHydraulic conductivityCurrent (fluid)Flow measurementSoil scienceMeasure (data warehouse)Analytical Chemistry (journal)MineralogyMechanicsGeologySoil waterComposite materialNanotechnologyChemistryElectrical engineeringComputer sciencePhysicsChromatography

Abstract

fetched live from OpenAlex

We describe an apparatus designed to perform streaming potential and resistivity measurements on unconsolidated soil samples. The apparatus enables the use of both unidirectional and oscillatory flow methods to measure the streaming potential coupling coefficient (C); the direct current resistivity method is used to measure the bulk resistivity (rho) of the soil sample. Measuring both of these parameters on the same sample under the same conditions enables us to properly characterize the streaming current cross-coupling coefficient (L). The apparatus is designed to test reconstituted saturated soil samples up to a maximum grain size of 9.5 mm, and hydraulic gradients from less than 0.1 up to a maximum of 4 m of H(2)Om in flow-through experiments. Excellent agreement between C values measured using the unidirectional and oscillatory flow methods validates the oscillatory flow method for unconsolidated samples.

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)0.002
metaresearch head score (Gemma)0.002
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: Methods · Consensus signal: Methods
Teacher disagreement score0.008
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0080.006

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 head0.043
GPT teacher head0.285
Teacher spread0.242 · 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
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

Citations13
Published2007
Admission routes2
Has abstractyes

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