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Record W1510453933 · doi:10.1002/0470848944.hsa076

Measuring Soil Water Content

2005· other· en· W1510453933 on OpenAlexaff
G. C. Topp, Ty PA Ferré

Bibliographic record

VenueEncyclopedia of Hydrological Sciences · 2005
Typeother
Languageen
FieldEnvironmental Science
TopicSoil Moisture and Remote Sensing
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsReflectometryGround-penetrating radarWater contentMetreRemote sensingEnvironmental scienceRadarNeutron probeSoil scienceTime domainGeologyComputer scienceGeotechnical engineeringNeutronPhysicsTelecommunications

Abstract

fetched live from OpenAlex

Abstract Major advances in the measurement of soil water content have arisen from electromagnetic (EM) methods that have developed rapidly in the last 20 years. Estimates of water content from EM measurements make use of the large relative permittivity of water compared to other soil components. Time domain reflectometry (TDR) and capacitance approaches use “probes” that convey signal into the soil and thus can measure principally the upper one‐meter depth. Ground penetrating radar (GPR) using noninvasive, transmitting, and receiving antennae possesses the capability to measure to even greater depths without causing soil disturbance. Remote radar and passive microwave methods, operating generally above 1 GHz, derive their information from within a few centimeters of the ground surface. Thermogravimetric and neutron moderation continue as viable long‐standing methods but are being used less as these methods are not amenable to data‐logging. The variety of instruments has increased the surface and near‐surface soil water measurement capabilities. Now it is possible for hydrologists to make informed choices among methods, and it is important to do so to optimize their study results.

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 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.566
Threshold uncertainty score1.000

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0110.001

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 head0.034
GPT teacher head0.222
Teacher spread0.188 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Citations20
Published2005
Admission routes1
Has abstractyes

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