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Record W4285268581 · doi:10.3808/jeil.202200082

Coupled Hydraulic-Thermal Model for Soils under Extreme Weather in Cold Regions

2022· article· en· W4285268581 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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Environmental Informatics Letters · 2022
Typearticle
Languageen
FieldEngineering
TopicSoil and Unsaturated Flow
Canadian institutionsUniversity of Regina
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Regina
KeywordsEnvironmental scienceExtreme ColdSoil waterHeat fluxExtreme weatherHydrology (agriculture)Spring (device)Atmospheric sciencesClimatologyFlux (metallurgy)Atmosphere (unit)Climate changeMeteorologyHeat transferGeologySoil scienceGeographyGeotechnical engineeringOceanography

Abstract

fetched live from OpenAlex

Extreme weather conditions govern the hydraulic and thermal properties of glacial clay deposits under the cold climate of the Canadian Prairies. The prediction of time-dependent soil behavior over the entire year and under extreme weather conditions is required for the design and construction of buried infrastructure. The main contributions of this research are the development and validation of a coupled soil-atmosphere interaction model to predict transient water and heat movement under mean, extreme dry, and extreme wet weather scenarios. Results indicated that the hydraulic properties are governed by the net water flux that resulted in the shifting of the seasons as follows: mean that comprises winter (3½ months), spring (1 month), summer (5½ months), and fall (2 months); dry that includes spring (4 months), summer (4 months), and fall (4 months); and wet that has winter (4 months), inseparable springsummer (5 months), and fall (3 months). The thermal properties are governed by air temperature for the investigated soil. Identical values of thermal gradient during spring-summer (April to October) in all scenarios indicate that the soil gains more heat compared with the heat loss during fall-winter (November to March), especially for mean and dry conditions. Furthermore, the inflection points in heat flux show that the soil gains heat from May to August and loses heat from September to April. Finally, the active depth of soil was found to be 4 ± 1 m for hydraulic properties and 3 m for heat flux.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.046
Threshold uncertainty score0.518

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 head0.017
GPT teacher head0.189
Teacher spread0.172 · 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