Bibliographic record
Abstract
Opened to traffic on 1 July 2019, the new Samuel De Champlain Bridge represents one of the largest infrastructure projects in North America. The rapidly deteriorating condition of the original Champlain Bridge in Montréal led the Government of Canada to accelerate its replacement and ultimately awarded a contract to the Signature on the Saint Lawrence Group, in 2015, to deliver a new replacement crossing. The project was fast-tracked, with a schedule of only 48 months from design to bridge opening. Due to its geographical location, this lifeline structure faces unique hazards including extreme cold temperatures, ice abrasion, de-icing salt attacks, wind, vessel collision, scour and seismic, while meeting its design life of 125 years. Sustainability and durability are also important project requirements. The 3.4 km long bridge is comprised of three independent structures: the 529 m long, asymmetric cable-stayed bridge (which features a single 169 m high tower), the 762 m long east approach and the 2044 m long west approach. The owner used a public–private partnership procurement model and the project was delivered using the design–build delivery method. An overview of this Can$2.4 billion mega project is provided in this paper, and the design and build solutions to overcome the suite of technical and schedule challenges are discussed.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.091 | 0.010 |
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".