Utah Transit Authority to Add 70 Miles of Rail in the Next Seven Years
Bibliographic record
Abstract
Utah is one of the fastest-growing states in the United States. This population growth will mean more travel demand and increased traffic congestion, especially in the long and narrow urban area known as the Wasatch Front. To meet these challenges, local elected officials along the Wasatch suggested accelerating Utah Transit Authority's (UTA) long-range transportation plan. In 2006, residents approved a quarter-cent sales tax increase to finance 70 mi of light rail and commuter rail as outlined in the long-range plan. These 70 miles make up UTA's Front Lines 2015 project, which consists of five light rail and commuter rail lines. All five projects will be in operation by 2015, 15 years ahead of the original schedule. Lines will offer several benefits to Utah residents, including increasing economic prosperity, reducing fuel costs and pollution, improving mobility for persons with disabilities, and providing jobs.
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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 | 0.000 | 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".