Preventive Maintenance Intervals for Transit Buses
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 synthesis studied preventive maintenance measures taken by a sampling of transit agencies to ensure buses are on time, protect taxpayer investments, and promote passenger satisfaction and public safety. The synthesis is offered as a primer for use by maintenance managers and other interested transit agency staff, as well as state and metropolitan transportation and planning agency staff, university educators, and students, to help lessen the number of inconvenienced passengers and the potential for safety-related incidents. Case studies reported on an automated onboard bus monitoring system, a technician certification program, and a review of challenges faced by a transit agency dealing with a diverse fleet mix. The study revealed how preventive maintenance intervals and activities were established at different agencies, understanding that each has a different fleet makeup, operating environment, and maintenance philosophy. This synthesis is based on the results of a survey questionnaire received from transit agencies in the United States and Canada, a literature review, and telephone survey interviews conducted with three transit agencies as case studies.
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 | 0.008 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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