Enhanced Parametric Railway Capacity Evaluation Tool
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
Many railroad lines are approaching the limits of practical capacity, and estimated future demand is projected to increase 84% by 2035. Therefore, identifying a good multiyear capacity expansion plan has become a particularly timely and important objective for railroads. An enhanced parametric capacity evaluation tool has been developed to assist railroad companies in capacity expansion projects. This evaluation tool is built on the Canadian National Railway Company parametric model by incorporating enumeration, cost estimation, and impact analysis modules. Based on the subdivision characteristics, estimated future demand, and available budget, the proposed tool will automatically generate possible expansion alternatives, compute line capacity and investment costs, and evaluate their impact. For a particular subdivision, there are two outputs from this decision support tool: a plot that depicts the delay–volume relationship for each alternative and an impact and benefit table that shows the impact of the future demand on the subdivision with different upgrading alternatives. The decision support tool is highly beneficial for budget management of North American railroads.
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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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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