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Record W2133631529 · doi:10.1109/eicccc.2006.277271

Adaptation Strategies for Road Embankments on Permafrost Affected by Climate Warming

2006· article· en· W2133631529 on OpenAlexaffabout
German Ciro, Marolo Alfaro

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsPermafrostClimate changeEnvironmental scienceHuman settlementGlobal warmingLeveeGeotechnical engineeringGeologyGeography

Abstract

fetched live from OpenAlex

Road embankments in Northern Manitoba experience lateral spreading and settlements that result in longitudinal cracking of road surfaces. Highways and road embankments can degrade permafrost because their construction and use increase the ground thermal regime beneath the embankments. In addition climate warming trend is likely to magnify this problem. When thawed, the permafrost beneath the road embankments results in differential settlements and dips, which contribute to a concern of public safety. A thermal modeling to reproduce the conditions and trends in the ground beneath road embankments in areas of discontinuous permafrost in Northern Manitoba was used as basis for assessing the impacts of climate change. Based on the simulated impact of climate change to the permafrost, a stress-deformation analysis was performed to determine the deformation and stability of the embankments with and without mechanical stabilization of the degrading permafrost.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.084
Threshold uncertainty score0.168

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.030
GPT teacher head0.249
Teacher spread0.218 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations5
Published2006
Admission routes2
Has abstractyes

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