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Record W2040355178 · doi:10.1139/t11-036

Determination of thermal diffusivity of soil using infrared thermal imaging

2011· article· en· W2040355178 on OpenAlex
Jayantha Kodikara, Pathmanathan Rajeev, Nicholas. J. Rhoden

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCanadian Geotechnical Journal · 2011
Typearticle
Languageen
FieldEnergy
TopicGeothermal Energy Systems and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsThermal diffusivityGeotechnical engineeringThermalInfraredThermographyEnvironmental scienceMaterials scienceGeologyOpticsPhysicsThermodynamics

Abstract

fetched live from OpenAlex

Despite its use in several fields, infrared thermal imaging is not yet commonly used in investigations of temperature-related problems in geotechnical engineering. This study provides a new approach to determining the thermal diffusivity of soil, using infrared thermal imaging under controlled laboratory conditions. Subject to one-dimensional heat flow conditions, an axial heat flow method is used to back-calculate the soil thermal diffusivity. The method has been applied on four compacted kaolin soil beams in transient conditions to back-calculate the thermal diffusivity of the soil. Reasonable agreement has been obtained between back-calculated and estimated thermal diffusivity values of kaolin. The study highlights the potential of use of thermal imaging for geotechnical applications.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.453
Threshold uncertainty score0.796

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)0.0010.000

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 head0.022
GPT teacher head0.225
Teacher spread0.204 · 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