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Record W1895817070 · doi:10.4141/cjss09120

Soil ice content measurement using a heat pulse probe method

2011· article· en· W1895817070 on OpenAlexaffvenue
Gang Liu, Bingcheng Si

Bibliographic record

VenueCanadian Journal of Soil Science · 2011
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsWater contentThermal conductivityMaterials sciencePulse durationPulse (music)Analytical Chemistry (journal)Volume (thermodynamics)Line sourceMineralogyComposite materialChemistryGeotechnical engineeringThermodynamicsGeologyOpticsPhysicsChromatography

Abstract

fetched live from OpenAlex

Liu, G. and Si, B. C. 2011. Soil ice content measurement using a heat pulse probe method. Can. J. Soil Sci. 91: 235–246. Measuring the volume-based ice content (θ i ) and thermal conductivity (k) of frozen soil is important for modeling energy and water balance of the earth's surface. The objective of this study was to examine whether a heat pulse probe (HPP) method can be used to measure soil ice content. To minimize ice melting, a heat pulse of duration of 60 s and strength of q′≈25 W m −1 was used for a HPP in frozen sands at various temperatures (T). For a 60-s heating duration, we compared the infinite line source (ILS) solution and finite line source solution with the solution of finite sample size and finite line source through simulations. The simulation suggested that a 60-s heating duration for ILS can be used for long heater probes in infinite media, or short probes in finite size samples in containers made of thermally insulating materials. In this study, sands were packed in small containers with heat pulse probes and a 60-s heating duration, and ILS were used for ice content estimation. Our results suggest that the HPP method has limited use in frozen soil. For sands with a mean grain size of 0.41 mm and 2.13 mm, there were good agreements between the HPP measured and gravimetric θ i values at temperature below −22°C and −18°C, respectively. However, above these temperatures, ice melting was significant and would lead to overestimation of θ i . The higher the initial temperature, the larger the overestimation of θ i .

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.328
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.258
GPT teacher head0.274
Teacher spread0.016 · 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.

Study designObservational
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

Citations52
Published2011
Admission routes2
Has abstractyes

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