Bibliographic record
Abstract
Most of the existing bridges in Montreal have not been designed to resist seismic forces. Although Montreal is not as highly exposed to earthquake hazards as New Zealand, Japan, California, or Vancouver, seismic hazards do exist. Seismic retrofitting has been considered as the most appropriate way to mitigate seismic hazards except for bridges that have a high retrofit cost and rather low importance. As the first step in seismic retrofitting, prioritization of bridges becomes a very important activity. The goal of this thesis is to upgrade the current Canadian prioritization procedure using the latest information from the performance of bridges during recent earthquakes, as well as results from the latest research projects. The previous procedure used in Canada was developed in 1993, since then many changes have occurred relative to seismic retrofitting philosophy. An analytical procedure has replaced the previous simple numerical scoring procedure for the evaluation of vulnerability, and the evaluation of the importance of a bridge has also changed significantly, especially with the addition of new factors such as the ratio of replacement cost to retrofit cost, structure condition and remaining service life. The proposed procedure incorporates these new features and is applied and compared to eleven other procedures for twenty-four bridges administered by the Montreal Office of Transport Quebec.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".