Bibliographic record
Abstract
This paper describes an Intersection Control Study (ICS) undertaken for the intersection of Sawmill Road, Katherine Street and Crowsfoot Road. The location is the Township of Woolwich in the Region of Waterloo in southern Ontario. The intersection is of an unusual configuration in that Katherine Street and Crowsfoot Road both intersect the north side of Sawmill Road. Travelling clockwise, angles between legs are approximately 55 degrees between Sawmill Road, Katherine Street and Crowsfoot Road, and 70 degrees between Crowsfoot Road and Sawmill Road. Katherine Street and Crowsfoot Road are under stop control supplemented by overhead flashing beacons. Motorists on Crowsfoot Road must stop, then stop gain on Katherine Street before entering Sawmill Road. The configuration also allows high-speed turns from Sawmill Road. Skew angles are inherently a safety risk: research documented in the Highway Safety Manual (AASHTO, 2010) indicates a 28% increase in collision potential for a skewed approach at a four-way intersection on a rural two-lane highway compared to a rightangle intersection. As can be expected, collision frequency at this location is higher than for four-way intersections elsewhere in the Region of Waterloo with similar traffic volumes. Traffic growth forecasted by the Region will warrant the installation of traffic signals. Because of this, and the safety problems being experienced, an Intersection Control Study (ICS) was undertaken as per Region of Waterloo policy.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".