TRAVIS Multi-Jurisdictional Oversize Vehicle Permitting System
Bibliographic record
Abstract
In Alberta, oversize vehicles require both provincial and municipal approvals, so carriers often require multiple transactions for each move. The TRAVIS (Transportation Routing and Vehicle Information System) Multi-Jurisdiction (MJ) permitting system was developed by Alberta Transportation to support industry's need for a simplified permitting process. TRAVIS provides a single point of contact for applicants, with multi-point approvals. The MJ permitting process begins with a client submitting an application using TRAVIS Web. The application includes carrier information, dates, vehicle data and requested route. TRAVIS can generate an optimal route if required. TRAVIS contains bridge capacities, dimensional, road ban and construction restriction data, and applies the restrictions as required. TRAVIS runs the application data through the business rule module and decides if it can be auto-approved or requires manual review. TRAVIS Proper is used for provincial reviews. Once provincial approval is granted, municipal business rules are applied to decide on automatic or manual review. If municipal review is required, municipalities review the application in MJ, adding conditions as required and approving or rejecting the application. TRAVIS produces a single permit document, including all approvals and conditions, saving industry and enforcement the effort of managing multiple documents. TRAVIS processed over 158,000 permits in 2010. Future enhancements include further web-based tools and expansion to include utilities, railroads and resource companies in the permitting process. Alberta is interested in partnering with interested governments to promote and expand the use of TRAVIS. TRAVIS or compatible permitting systems could facilitate expanding the multi-jurisdiction concept to inter-provincial travel. (A) For the covering abstract of this conference see record control number 201111RT334E.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.072 | 0.045 |
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".