Bibliographic record
Abstract
Speed management is not necessarily about reducing speed, but to a considerable extent about planning and designing the road layout and the road network in such a way that an appropriate speed is obtained. The main objective of this report was to develop recommendations for speed management strategies in our country. Safety researches related to speed was reviewed on the basis of literature studies. Also, spot speed characteristics by several road type was analyzed and speed management methods in several country are described briefly. Outlines of speed management in our country are on eliminating over speeding drivers, reducing average running speed and standard deviation, and mitigating the stop and go conditions. For this, five main strategies are recommended, that is, speed management plan for road user, consistent speed management by road types, acceptance of various traffic calming techniques, improvement driver’s awareness for speeding, and advancement of enforcement techniques. For more refined strategies, comprehensive road safety research related to speed is to be need, including speed-safety relationships, factors affecting drivers’choice of speed and development of and engineering and enforcement measures to manage speed. And an inter-agency speed management team to work on this safety issue to be review, like USA and Canada.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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; both teacher heads agree on what is shown here.
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".