MétaCan
Menu
Back to cohort
Record W7047079077

Field and numerical studies of an arctic highway embankment compacted with frozen fill over permafrost

2019· dissertation· en· W7047079077 on OpenAlexaboutno aff

Bibliographic record

VenueMspace (University of Manitoba) · 2019
Typedissertation
Languageen
FieldEngineering
TopicSuperconducting Materials and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsPermafrostLeveeArcticInstrumentation (computer programming)Numerical modelsNumerical modeling
DOInot available

Abstract

fetched live from OpenAlex

Highway embankments in arctic regions are constructed during winter because 1) of ease in moving fill materials, 2) to preserve the permafrost, and 3) to minimize environmental impact. This means that the fill is often frozen during compaction. There is uncertainty about the performance of embankments in arctic regions that are compacted with fill that is initially frozen and then experiences natural thawing during subsequent summers. This study will look into the performance of a highway embankment test section in the newly-constructed Inuvik-Tuktoyaktuk Highway in the Northwest Territories, Canada. Numerical modeling of the embankment temperatures and deformations were calibrated with measurements from the field instrumentation over the first thawing season. The calibrated numerical models were used to investigate important factors affecting the performance of the embankment during and shortly after construction.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.956
Threshold uncertainty score0.088

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.017
GPT teacher head0.221
Teacher spread0.205 · 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 designObservational
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

Citations1
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueMspace (University of Manitoba)Same topicSuperconducting Materials and ApplicationsFrench-language works237,207