Passenger Rail Planner's Guide 2008
Bibliographic record
Abstract
Rail Planner's Guide for 2008 begins with an article titled Passenger rail: A national priority in which the author describes a rail renaissance for the U.S. which is promoting rail as a viable alternative to the dependence on automobile. article mentions two studies by the American Public Transportation Association (APTA) which look at commuter and intercity passenger rail as well as potential high speed rail operations in the U.S. Analyses are presented for Amtrak through an essay titled Amtrak's fleet: the next great step, as well as another essay titled Shaping the freight/passenger rail interface. Also included is a chart identifying FY 2009 funding for New Starts projects and Small Starts projects. final section, titled The North American passenger rail market, first presents updates on Amtrak and VIA Rail Canada. This is then followed by an overview of passenger rail systems in Boston, Connecticut, the New York Metropolitan Area, New Jersey, Philadelphia, Pittsburgh, the Baltimore-Washington Metropolitan Area, Norfolk, Raleigh, Charlotte, Atlanta, Orlando, Tampa, Miami, Buffalo, Cleveland, Chicago, Minneapolis/St. Paul, St. Louis, Nashville, Memphis, Little Rock, New Orleans, Dallas-Fort Worth, Houston, Austin, Denver, Salt Lake City, Albuquerque, Phoenix, San Diego, Los Angeles, San Jose, San Francisco, Stockton, Sacramento, Portland, Seattle-Tacoma, Vancouver, Edmonton, Calgary, Toronto, Ottawa, and Montreal.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.463 | 0.355 |
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".