Assessment of low temperature exposure for design and evaluation of elastomeric bridge bearings and seismic isolators in Canada
Bibliographic record
Abstract
This paper presents key data and relevant analyses assessing low temperature exposure for design and evaluation of elastomeric bridge bearings and isolators in Canada. A large database of temperature records is processed to investigate the potential for instantaneous thermal stiffening and crystallization. The results mainly show that: (i) temperature conditions at some locations lead to a significant potential for instantaneous stiffening in terms of intensity and frequency; (ii) in warmer locations, thermal stiffening is highly improbable; (iii) the number of consecutive days below a given low temperature is very variable geographically; and (iv) the crystallization testing criteria prescribed in CSA S6-14 can be too conservative. The results are also illustrated using contour maps. Important differences in temperature variation trends between eastern and western Canada are highlighted. The proposed methodology and obtained results constitute efficient tools to determine site-specific temperature conditions for enhanced performance-based design and evaluation of bridges in Canada.
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How this classification was reachedexpand
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".