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Record W2529735959 · doi:10.1002/ppp.1919

Adaptation Methods for Transportation Infrastructure Built on Degrading Permafrost

2016· article· en· W2529735959 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

VenuePermafrost and Periglacial Processes · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPermafrostContext (archaeology)Environmental scienceGlobal warmingClimate changeCivil engineeringEngineeringGeology

Abstract

fetched live from OpenAlex

Abstract Climate warming since the second half of the 20 th century has begun to significantly impact infrastructure integrity in permafrost environments and has already resulted in expensive maintenance operations. Engineers in countries with permafrost are actively working to adapt the design of structures to degrading permafrost conditions. Here, we review permafrost degradation processes and their geotechnical impacts. We also summarise mitigation techniques for protecting transportation infrastructure built on permafrost and for preventing permafrost degradation near these facilities based on the results of field and laboratory tests, numerical simulations and engineering practices on such infrastructure. We draw four conclusions: (1) climate warming and local surface changes have caused permafrost degradation, and resulted in instability and damage leading to infrastructure maintenance and repair; (2) passive cooling methods, including high‐albedo surfacing, sun‐sheds, air convection embankments, air ducts, heat drains and thermosyphons, have shown consistent cooling effects, if designed appropriately; (3) mitigation and adaptation methods are more expensive than conventional construction techniques as shown by construction cost data for a test site in Canada; and (4) the influence of continued climate warming on permafrost and infrastructure design must be considered within the design of new or rehabilitated infrastructure and within the context of the infrastructure's service life. Copyright © 2016 John Wiley & Sons, Ltd.

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 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 score0.472
Threshold uncertainty score0.999

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 communication0.0000.001
Open science0.0000.000
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 head0.047
GPT teacher head0.314
Teacher spread0.267 · 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