THE ECONOMICS OF HORIZONTAL CURVES : AN ANALYSIS OF THE EFFECTS OF IMPROVEMENTS TO HORIZONTAL ALIGNMENT ON RURAL HIGHWAYS
Bibliographic record
Abstract
This paper was presented at the session titled 'Risk management in the roads sector - geometric design'. The functional design of highways is a process that relies on both quantitative data, such as capital and maintenance costs, as well as more qualitative data, such as safety and road user costs. While the former considerations are usually relatively well-defined by the physical characteristics of the project, the latter inputs to the functional design process are often the subject of much debate and research among highway professionals. This paper details the results of a research project aimed at better defining the more subjective effects of a specific aspect of roadway improvements, namely those which eliminate or reduce transitions in horizontal alignment. The objective of this research project is to provide recommendations for improving Saksatchewan Highways and Transportation's ability to incorporate the effects of horizontal curves on the motoring public into its assessment of the benefits and costs associated with a given project or route. While these implications include travel time delays and vehicle operating costs, the most significant factor to be defined is the effects of horizontal curves on traffic safety. This project was, thus, expressly designed in order to improve th effectiveness of the analysis of the benefits and costs associated with various routings and alignments of rural highways in Saskatchewan. For the covering abstract of this conference see ITRD number E200883. (A)
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 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) | 0.008 | 0.000 |
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".