Bibliographic record
Abstract
This book includes only public transportation data and excludes taxicab, unregulated jitney, school, sightseeing, intercity, charter,\nmilitary, and non-public service (e.g., governmental and corporate shuttles), and special application systems (e.g., amusement\nparks, airports, and the following types of ferry service: international, rural, rural interstate, island and urban park).\nData are based on the annual National Transit Database (NTD) report published by the United States Government's Federal Transit\nAdministration (FTA). APTA supplements these data with special surveys. Where applicable, data are calculated based on 2000\nU.S. Census Bureau urbanized area population categories.\nBecause data are reported to the NTD based on transit agency fiscal years rather than calendar years, data listed for a particular\nyear are necessarily extrapolations of the sum of data reported for all fiscal years ending in a particular calendar year. All Canadian\ndata are based on calendar years.\n
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.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.227 | 0.222 |
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".