Learnings from the past to design metallic bridges spanning centuries into the future
Bibliographic record
Abstract
Since the 20thcentury, modern bridges have been typically designed for a relatively short design life of either 100 or 120 years. In reality, there are numerous examples of bridges that are over 100 years old that are still in service today. In some cases, these bridges have heritage protection status. In other cases, they are a vital link to their transportation network, for which any disruptions will result in significant economic impact to the local or regional economy. Over the years, the authors have been involved with the inspection, maintenance, and refurbishment of historic bridges. This paper provides an overview of lessons learnt from examples of historic metallic bridges in New Zealand and the United Kingdom, as well as present the case for a 200-year bridge. Lessons learned from failures in design and detailing for durability, material selection, and allowance for future access for inspection and maintenance can be used when designing new bridges, with the aim to minimize future maintenance cost and assisting 21stcentury bridges to span centuries into the future.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".