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Record W4400989833 · doi:10.69554/dfva6205

History, survey, conservation and repair of the Royal Naval Magazine of Cole Island, Esquimalt Harbour, Vancouver Island, British Columbia, Canada

2023· article· en· W4400989833 on OpenAlexaboutno aff
Nigel Copsey

Bibliographic record

VenueJournal of building survey, appraisal & valuation · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicMaritime and Coastal Archaeology
Canadian institutionsnot available
Fundersnot available
KeywordsHarbourGeographyArchaeologyHistoryOceanographyGeology

Abstract

fetched live from OpenAlex

This paper is a brief summary of the history of the evolution of the magazine in Esquimalt Harbour that served the Royal Navy’s Pacific Squadron, based in the same harbour after 1862 and which was intimately entwined with the development of the British colony of Vancouver Island after its foundation by the Hudson’s Bay Company (HBC) during the 1840s. It also chronicles the conservation, repair and informed restoration of the magazine site over the last ten years, in which latter endeavour the author became periodically involved after 2014, culminating in a five-month stay upon the island, as resident mason-conservator and default caretaker, between July and November 2021. The paper draws upon the author’s original 2014 condition survey, and upon a paper ‘Lime in Canada’ written by the author for the Building Limes Forum Journal in 2020, while incorporating subsequent research and additional material and correcting some of the errors and omissions in both earlier accounts. The project was driven by the deployment of traditional skills and like-for-like materials within the modern western Canadian context, within which such skills and such an approach are scarce, seeking to demonstrate the benefits of these to the built heritage across the province of British Columbia and to encourage their widespread use for the conservation and repair of traditional buildings in the province.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.442
Threshold uncertainty score0.675

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
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)0.0010.000

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 head0.031
GPT teacher head0.241
Teacher spread0.210 · 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 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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

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