Modeling Operating Speed and Speed Differential on Two-Lane Rural Roads
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The geometric features of a highway network play a significant role considering the fact that collisions occur disproportionately on horizontal curves. Based on extensive literature review, the problem mainly stems from the lack of geometric design consistency–conformance of highway geometric characteristics with drivers’ expectations. More specifically, drivers select their speeds according to their own perception of the road (referred to as the operating speed) rather than the designer’s perception (referred to as the design speed). To address operating speed consistency evaluation in Canada, two sets of models for speed behavior were examined based on speed data collected using traffic counters/classifiers on 20 curves on two-lane rural highways in Ontario. Relatively weak relationships were developed for the traditional operating speed on horizontal curves, while stronger relationships were found for the 85th percentile speed differential from a tangent to a curve. It was also shown that the nonintrusive approach for speed data collection might reveal different speed behavior than that observed using radar guns.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it