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Prince of Wales Fort: Structural Wall Analysis

2010· article· en· W1969926571 on OpenAlexaffabout
Andrea C. Isfeld, Nigel G. Shrive

Bibliographic record

VenueAdvanced materials research · 2010
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicBuilding materials and conservation
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsRubbleMortarMasonryGeologyCohesion (chemistry)Geotechnical engineeringSpring (device)ArchaeologyEngineeringGeographyOceanographyStructural engineering

Abstract

fetched live from OpenAlex

The Prince of Wales Fort, in Churchill Manitoba, was constructed in the early 18th century by the Hudson Bay Trading Company (HBC) in an effort to secure the fur trade in northern Canada. The fort is a Vauban style rubble masonry construction, and is the most northerly fortification of this kind. In the 1920’s the fort received recognition as a National Historic Site by the Historic Sites and Monuments Board of Canada, at which time monitoring and repairs began under the leadership of Parks Canada. As a result of the fort’s northern latitude it has been subjected to extreme temperatures and freeze thaw cycles causing a gradual break down of the mortar within the escarp walls. Recently, climate change has led to an increase in the average local temperature shifting the thermal gradient within the earth rampart. During spring and summer, high volumes of ground water have drained through the walls washing out much of the degraded mortar. The result is a partially grouted rubble wall, encased with ashlar face stones. These deteriorating core conditions have caused significant lateral deflections in several areas and failure in others. The core wall material will be analyzed by modeling it as an irregular granular material. Using this approach, different levels of cohesion can be used to determine the in-situ mortar conditions and the strength of the structure.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.422
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0050.000

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 head0.032
GPT teacher head0.328
Teacher spread0.296 · 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.

Study designBench or experimental
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

Citations0
Published2010
Admission routes2
Has abstractyes

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