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Record W4387098781 · doi:10.1186/s40703-023-00196-9

Numerical simulation of ground thermal response in Canadian seasonal frost regions to climate warming

2023· article· en· W4387098781 on OpenAlexafffundabout
Mohammed Yassir Marrah, Mamadou Fall, Husham Almansour

Bibliographic record

VenueInternational Journal of Geo-Engineering · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsNational Research Council CanadaUniversity of Ottawa
FundersNational Research Council Canada
KeywordsFrost (temperature)Climate changeEnvironmental scienceGlobal warmingClimatologyClimate modelEffects of global warmingAtmospheric sciencesMeteorologyGeographyGeology

Abstract

fetched live from OpenAlex

Abstract To ensure that public infrastructure can safely provide essential services and support economic activities in seasonal frost regions, the design of their foundation systems must be updated and/or adapted to the impacts of climate change. This objective can only be achieved, if the impact of global warming on the soil thermal behaviour in Canadian seasonal frost regions is well-known and can be predicted. In the present paper, the results of a modeling study to assess and predict the effect of global warming on the thermal regimes of grounds in three Canadian seasonal frost regions (Ottawa, Sudbury, Toronto) are presented and discussed. The results show that future climate changes will significantly affect the soil thermal regimes in seasonal frost Canadian areas. The simulation results indicated a gradual loss in the frost penetration depth due to the climate change, in the three representative sites. The frost period duration will be shorter due to climate change in the three selected regions and will completely disappear in Ottawa and Toronto. However, the impact of climate change would not appear clearly in the first 40 years “up to 2060”. The response of the ground to the effect of climate change is a function of the geotechnical characteristics of the ground and the climate conditions. The numerical tool developed and results obtained will be useful for the geotechnical design of climate-adaptive transportation structures in Canadian seasonal frost areas.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.444
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.028
GPT teacher head0.269
Teacher spread0.241 · 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 designSimulation or modeling
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

Citations4
Published2023
Admission routes3
Has abstractyes

Explore more

Same venueInternational Journal of Geo-EngineeringSame topicClimate change and permafrostFrench-language works237,207