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Record W4404182045 · doi:10.1016/j.prostr.2024.09.255

Planning for SHM in the conservation of places of faith: the case study of a Saint John, NB cathedral

2024· article· en· W4404182045 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueProcedia Structural Integrity · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicCultural Heritage Management and Preservation
Canadian institutionsUniversity of New BrunswickUniversity of Toronto
Fundersnot available
KeywordsSAINTFaithSociologyPhilosophyHistoryTheologyArt history

Abstract

fetched live from OpenAlex

Many churches, temples, and mosques stand as cherished heritage structures, embodying the rich cultural essence of communities worldwide. Monitoring and maintaining these structures often demand unique considerations due to their distinctive features and materials. Provided in this paper is a review of sensors used in the SHM of 45 historic places of faith through discussions of sensor benefits, limitations, rational, and deployment locations across different building types. This review is contextualized via a case study of the Cathedral of the Immaculate Conception in Saint John, NB, Canada. Following a brief history of the cathedral, complications due to previous conservation efforts are discussed and the cathedral’s present state is described. Then, the sensor selection process for phases one and two of a cost-effective SHM implementation is presented. Finally, the staging and timing of sensor installation is detailed. This SHM system is expected to assist in timely damage detection and condition-based maintenance, minimising the cost of interventions.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.158
Threshold uncertainty score0.990

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.183
GPT teacher head0.331
Teacher spread0.148 · 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