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Record W1965397587 · doi:10.1109/icgpr.2010.5550068

Comparing electromagnetic induction and ground penetrating radar techniques for estimating soil moisture content

2010· article· en· W1965397587 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicGeophysical Methods and Applications
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsLoamGround-penetrating radarWater contentSoil scienceSiltGeologyRadarSoil waterHydrology (agriculture)Environmental scienceRemote sensingGeotechnical engineeringGeomorphology

Abstract

fetched live from OpenAlex

Previous studies have demonstrated the capacity of electromagnetic geophysical methods for estimating soil moisture content. In this study, electromagnetic induction (EMI) and ground-penetrating radar (GPR) measurements were coincidently collected along a fixed survey line to evaluate temporal changes in apparent electrical conductivity and electromagnetic direct ground wave velocity, respectively; surveys were collected at three sites (i.e., sand, sandy loam and silt loam) during the course of a complete annual cycle of soil conditions. These two geophysical data sets correlated well during the course of the annual cycle at the silt loam site. Correlation between the two data sets was not as strong at the other two sites, with the sand site showing the lowest correlation values. Further, the geophysical data and gravimetric water content measurements obtained from the upper 0.5 metres indicate higher correlation estimates at the finer grained silt loam site relative to the sand and sandy loam sites.

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)0.000
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 score0.617
Threshold uncertainty score0.330

Codex and Gemma teacher scores by category

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

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 head0.030
GPT teacher head0.268
Teacher spread0.237 · 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

Quick stats

Citations8
Published2010
Admission routes2
Has abstractyes

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