Sustainability and Visual Considerations for Footbridges Designed with Stainless Steel
Bibliographic record
Abstract
Despite the impact that stainless steel has had in the architecture, industrial applications and multitude of consumer products for more than 50 years, its presence in civil engineering structures is recent. Some interesting structures, mainly pedestrian bridges, have been built in the last two decades. Stainless steel creates a light, strong, corrosion-resistant, and elegant structure with premium aesthetics. The extended structure life-cycle typically offsets the higher capital cost of stainless steel due to the increased corrosion resistance and reduced maintenance, which in turn reduces the overall cost of ownership. This represents a net advantage for the asset owner and improves safety and long-term durability. Stainless steel is recognized as a sustainable material with a lower environmental impact, lightweight construction, and low maintenance and deconstruction cost over the bridge lifespan. Stainless steel is one of the highest recycling rates of any material. This paper provides an overview of the sustainability and visual considerations for footbridges designed with stainless steel through a recently built example: the Garrison Crossing in Toronto.
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.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".