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Record W2019650838 · doi:10.1029/1999wr900291

Identifying the conditions amenable to the determination of solute concentrations with time domain reflectometry

2000· article· en· W2019650838 on OpenAlex

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

VenueWater Resources Research · 2000
Typearticle
Languageen
FieldEngineering
TopicGeophysical Methods and Applications
Canadian institutionsUniversity of SaskatchewanUniversity of Waterloo
Fundersnot available
KeywordsReflectometryElectrical resistivity and conductivityConductivitySoil waterMaterials scienceSoil scienceVolume (thermodynamics)Time domainAnalytical Chemistry (journal)Environmental scienceChemistryThermodynamicsEnvironmental chemistryPhysics

Abstract

fetched live from OpenAlex

On the basis of an analysis of the weighting of the bulk electrical conductivity along time domain reflectivity (TDR) probes we show theoretical limitations to the measurement of solute concentrations with TDR. Simple example calculations demonstrate that there will only be a unique relationship between the TDR‐measured electrical conductivity and the average solute concentration in the pore water under one of two conditions. First, if the water content is spatially uniform throughout the sample volume of the probe, TDR may be used to determine solute concentrations. Second, if the water content is spatially variable but the spatial distribution is temporally constant and the solute concentration is spatially uniform throughout the probe's sample volume, solute concentrations can be inferred from the electrical conductivity response. Further complications arise in soils with spatially variable porosities or surface electrical conductivities, making TDR unsuited to determining solute concentrations even if one of these conditions is met.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.663
Threshold uncertainty score0.629

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.042
GPT teacher head0.353
Teacher spread0.312 · 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