Bibliographic record
Abstract
A case study of the Design and Construction of the Chief Peguis Trail Extension Project in Winnipeg, Manitoba. This project was designed and constructed as a Private-Public-Partnership (P3) and the Contractor is responsible for maintenance for the next 30 years. The total time from award of the P3 contract to commissioning and opening the roadway was 15 months, approximately one year ahead of schedule. This fast-track schedule led to numerous challenges in staging and construction methods, particularly with numerous activities occurring simultaneously. The project length of 3.7 km included a 4-lane arterial divided roadway with a fly-over roadway grade separation, sewer and water relocations, new land drainage piping, a pedestrian bridge, noise attenuation walls, multi-use paths, berms and three new intersections. Throughout the design and construction, decisions were made based on construction efficiency while also considering life cycle cost and maintenance costs. Because of the fast-track schedule and because the P3 Contractor will be maintaining the roadway, the design and construction process was very dynamic, compared to a traditional Design- Bid-Build project. (A) For the covering abstract of this conference see ITRD number E201211RT334E.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".