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Record W2072504146 · doi:10.2136/vzj2005.0019

Solute Transport Measurement Under Transient Field Conditions Using Time Domain Reflectometry

2006· article· en· W2072504146 on OpenAlexaff
Kosuke Noborio, R. G. Kachanoski, C. S. Tan

Bibliographic record

VenueVadose Zone Journal · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicSoil Moisture and Remote Sensing
Canadian institutionsAgriculture and Agri-Food CanadaUniversity of Alberta
Fundersnot available
KeywordsReflectometryTRACERTransient (computer programming)CalibrationTime domainSoil scienceEvapotranspirationDrainageLysimeterField (mathematics)Flux (metallurgy)Environmental scienceMaterials scienceSoil waterPhysicsMathematics

Abstract

fetched live from OpenAlex

Measurement of transport properties of field soil remains a challenge. Time domain reflectometry (TDR) has been used for rapid and nondestructive measurement of the movement of conservative tracers in controlled laboratory and field experiments. Measuring transport under transient conditions in the laboratory using TDR has also been reported, but obtaining appropriate calibration relationships remains a challenge. We present a method for rapid and nondestructive measurement of field transport of an electrolytic tracer (applied to the soil surface) under transient rainfall and evapotranspiration conditions with net drainage using TDR without any a priori calibrations. The method uses TDR probes in plots with and without a tracer applied. The simultaneous TDR measurements of apparent impedance and dielectric constant in the paired plots were used to calculate the relative solute mass remaining to a given depth (i.e., TDR probe depth) as a function of time during a 270‐d field experiment under natural rainfall and evapotranspiration conditions of net drainage. The measurements give relative solute mass flux that is equivalent to the solute travel time probability density function.

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)0.001
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 score0.913
Threshold uncertainty score0.924

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.242
Teacher spread0.223 · 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 teacher head, 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

Citations12
Published2006
Admission routes1
Has abstractyes

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