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Record W1776006496 · doi:10.1139/cgj-2013-0313

Factors affecting soil permittivity and proposals to obtain gravimetric water content from time domain reflectometry measurements

2014· article· en· W1776006496 on OpenAlexvenueno aff
L.M. Thring, Daniel Boddice, Nicole Metje, Giulio Curioni, D.N. Chapman, Lleyton J. Pring

Bibliographic record

VenueCanadian Geotechnical Journal · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicSoil Moisture and Remote Sensing
Canadian institutionsnot available
FundersEngineering and Physical Sciences Research CouncilArts and Humanities Research Council
KeywordsWater contentSiltSoil waterSoil scienceReflectometryAtterberg limitsGeotechnical engineeringConsolidation (business)Environmental scienceBulk densitySubsoilTime domainGeologyGeomorphologyAccounting

Abstract

fetched live from OpenAlex

Time domain reflectometry (TDR) measures the apparent relative dielectric permittivity (ARDP) of a soil and is commonly used to determine the volumetric water content (VWC) of the soil. ARDP is affected by several factors in addition to water content, such as the soil’s electrical conductivity, temperature, and density. These relationships vary with soil type and are very soil-dependent, and despite previous research, they are still not fully understood. A multivariate statistical approach (principal component analysis, PCA) is used to describe a range of soils from two separate sites in the UK (clay and silty sand – sandy silt). The advantage of a PCA is that it considers several variables at a time, giving an immediate picture of their underlying relationships. It was found that for the studied soils, ARDP was positively correlated with VWC and bulk electrical conductivity, but did not show any dependence on some other geotechnical parameters. TDR has recently been used in geotechnical engineering for measuring the gravimetric water content (GWC) and dry density. However, the current approaches require a custom-made TDR probe and an extensive site specific empirical laboratory calibration. To extend the potential use of TDR in the geotechnical industry, three relatively simple methods are proposed to estimate the GWC from VWC (derived from the measured ARDP values) and dry density depending on the amount of information known about the soil. Examples of possible applications of these methods include continuous monitoring of consolidation adjacent to a structure, the effect of seasonal weather and climate change on ageing earthwork assets, and the shrink–swell potential adjacent to trees. All three methods performed well, with between 83% and 98% of the data lying within a ±5% GWC envelope, with the data for clay soils performing better than those for silty sands – sandy silts. This is partly due to the fact that the applied relationship converting ARDP to VWC performs better for clays than silty sands – sandy silts, as well as less variation of the estimated bulk density that is needed to derive the dry density.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.036
GPT teacher head0.236
Teacher spread0.200 · 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

Citations27
Published2014
Admission routes1
Has abstractyes

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