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Record W1996650025 · doi:10.2136/vzj2005.0099

Advances in Soil Water Content Sensing: The Continuing Maturation of Technology and Theory

2005· article· en· W1996650025 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

VenueVadose Zone Journal · 2005
Typearticle
Languageen
FieldEngineering
TopicGeophysical Methods and Applications
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsVadose zoneGround-penetrating radarReflectometryEnvironmental scienceRemote sensingWater contentSoil scienceComputer scienceGeologyHydrology (agriculture)RadarSoil waterTime domainGeotechnical engineeringTelecommunicationsComputer vision

Abstract

fetched live from OpenAlex

In what has become almost a tradition for Vadose Zone Journal , this special section, Soil Water Sensing, follows two related special sections: Advances in Measurement and Monitoring Methods (Vol. 2, Issue 4, 2003) and Hydrogeophysics, which also focused on measurement methods (Vol. 3, Issue 4, 2004). The tremendous interest in vadose zone monitoring reflects the intense societal interest in understanding our environment, the increasing comprehension of scale‐dependence of vadose zone properties and processes, and the rapid changes occurring in sensing methods. In this article, we present an overview of the papers, many of which detail methods that rely on soil electromagnetic (EM) responses, including time domain reflectometry (TDR), ground penetrating radar (GPR), and capacitance methods. The papers also indicate key aspects of sensor performance requiring improvement through further sensor development.

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 score0.729
Threshold uncertainty score0.111

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 head0.009
GPT teacher head0.227
Teacher spread0.219 · 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