Is the Current Level of Service of the Highway Network Financially Sustainable
Bibliographic record
Abstract
This paper discusses the challenges that were encountered by both Saskatchewan and Manitoba in developing life cycles for pavements that lead to the development of a Financial Sustainability Index for paved highway networks that is to be applied to highways in both provinces. The paper discusses the life cycle method used in the project and the sustainability index calculations. The intended use of the Financial Sustainability Index to support decision-making is also discussed. Initially the life cycle analysis was undertaken using performance and cost information from current Ministry pavement performance models. It rapidly became evident that those models are not sufficiently accurate to enable a proper life cycle to be undertaken. This led to revisions resulting in more consistent and rational models. Those models were then slightly modified again and form the basis for all of the life cycles performed during the second half of the project. The project uses whole of life costs that are annualized into an equivalent annual cash flow (EACF) per square metre of pavement. The annualized cost is then used to aggregate the whole of life costs for each network based on the proportion of the inventory that is within each condition state at the moment. Significant decisions about the long term levels of service underlie the life cycle costs (for the next 60 years). As there are significant differences based on various assumptions both agencies are putting effort into identifying benchmark life cycle profiles for each network class by condition state. Both Agencies intend to annually refine the benchmark profiles based on analysis of actual performance. Once both Agencies are able to accurately identify what the actual life cycles are then the sustainability index will be reported annually to accurately monitor funding levels for all classes of network for each year.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".