Capacity Modeling Guidebook for Shared-Use Passenger and Freight Rail Operations
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
This report provides technical guidance for state departments of transportation (DOTs) who are starting or expanding passenger rail service on privately-owned and shared-use rail corridors. The guidance is designed to aid in the DOTs’ understanding of the methods host railroads use to calibrate and apply capacity models to determine if adequate capacity exists to support new or increased passenger rail service or if infrastructure improvements may be necessary. A shared understanding of these methods will aid all parties—including state DOTs—in the negotiation of service outcome agreements. After an introductory chapter, the individual chapters present a synthesis of stakeholder input, analytical approaches to line capacity in shared-use corridors, best practices, and a discussion of recent and ongoing planning for the Chicago-Saint Louis high speed rail implementation on the Union Pacific Railroad and Canadian National Railway line. This report should be of immediate use to transportation professionals charged with the responsibility for planning passenger rail service and negotiating shared-corridor service agreements with host railroads.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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