Structural characterisation of Eastern Canada’s old industrial masonry buildings via typological analysis: part II – building database analysis
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.
Bibliographic record
Abstract
The typological analysis conducted in the companion paper is further expanded within this work through the critical analysis of a new extensive building database specifically conceived for old industrial masonry buildings in Eastern Canada. The identification of recurrent unreinforced masonry (URM) building archetypes in this low-to-moderate seismic region is essential to decrease uncertainties currently prevalent in the analysis of local old URM structures, often targeted for adaptive reuse. The database assembled herein comprises various heritage designated buildings across Eastern Canada and was compiled harmonising existing repositories at the federal, provincial and municipal level with an unprecedented focus on structural features. The characteristics of these resources are quantitatively analysed and applied to a case study of the city of Montréal, one of the most important industrial centres in nineteenth and twentieth century Canada. Outcomes from this study will guide practitioners and researchers involved in the structural and seismic assessment and retrofit of old industrial URM constructions, enable more and less invasive rational retrofit designs and inform the new Existing Structures provisions to be included in the 2030 National Building Code of Canada.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it