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
The views of Karen Rae, U.S. Federal Railroad Administration (FRA) deputy administrator, are presented in regard to how, in the coming decade, passenger rail will play a much greater role in U.S. transportation. In early 2010, $8 billion in grants will be allocated by the FRA as part of the Obama administration's American Recovery and Reinvestment Act (ARRA), beginning a new investment era in the country's intercity rail network, which has long been neglected. This includes high-speed rail projects, of which the FRA received 278 pre-applications for funding totaling $102 billion. Rae believes that a few very critical successes must be produced with stimulus funds, or else there will be no high-speed rail program. Rae believes it will only be necessary to have speeds of 300 km/h or greater on certain corridors, such as California. A figure illustrates designated high-speed corridors in the U.S., with extensions into Canada.
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 | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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