Bibliographic record
Abstract
The progress on the use of variable message signs (VMS) are discussed in this article. The article highlights the longest road tunnel in the Middle East, and the installation of the latest VMS technology in Canada’s oldest national park to help motorists traveling through. A large volume of VMS have been installed in the new 4.2km-long Zayed Street Tunnel in Abu Dhabi. The VMS supply consists of 204 lane control signs, with Red, Yellow and Green light emitting diodes (LED) pre-defined signs; 204 variable speed limit signs, with Red and Yellow LED signs; 13 in-tunnel VMS 32x480 pixels, Yellow/Amber LEDs; one in-tunnel VMS 32X304 pixels; 12 tunnel approach VMS 112x272 pixels, full color LEDS and the hardware and software control unit. Part of the $1.36 billion four-stage Zayed Street upgrade, which began in October 2007, around 20% of the 7,000 vehicles traveling through Zayed Street during peak week day hours (7am-9am, 3pm-5pm) are reportedly expected to use the new four-lane in each direction tunnel. This article also describes how a system of 3.4cm full-color Vanguard VF-2420 dynamic message signs is now featured on the Trans-Canada highway in Banff National Park, near Calgary, Alberta. Parks Canada and the Alberta Ministry of Transportation contracted with a firm to integrate the display system. The displays show variable weather-related messages to travelers as they ascend around 426.72m into the mountains from Calgary.
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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.138 | 0.041 |
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".