Design and Construction of the Deh Cho Bridge: Challenges, Innovation,and Opportunities
Bibliographic record
Abstract
The Deh Cho Bridge will be the first bridge structure crossing the Mackenzie, Canada's longest river. When the bridge is opened it will permanently replace ferry and ice road services along Highway 3 connecting Yellowknife in the Northwest Territories with Highway 1 in the South. The bridge's remote location in the North with severe winter conditions of up to -40 degrees C requires meticulous planning and is an extraordinary challenge for men and equipment. Innovative design methods led to the design of a unique 1045 m long continuous cable supported superstructure with expansion joints only at the abutments. The design employs ecological light-weight design principles as well as fast-tracked fabrication and erection methods. Structural performance of the superstructure has been optimized for construction and service scenarios allowing a high degree of repetition as well as aesthetic proportions and rhythm. Serious design challenges often require new philosophies and strategies. On the other hand, they provide exceptional opportunities for innovation. The Assembly-line Design Approach, the Failure Mechanism Concept, and the Fuse Design Philosophy have been specifically developed for the Deh Cho Bridge with the purpose to cope with extraordinary schedule and design requirements. (A) For the covering abstract of this conference see ITRD record number 201211RT334E.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".