Bibliographic record
Abstract
Abstract The electrical energy that powers the signal systems for railways is typically provided by commercial services adjacent or near the enclosures housing the signal equipment. In remote or areas of challenging terrain, railways have installed their own signal power lines to maintain a high level of reliability while lowering the cost of energy supply. These power lines are typically fed from a commercial power source and fed to the railway at a lower voltage (< 1KV). These lines are controlled from local manipulation of fuse cutouts and do not provide for any redundancy. When there is trouble on the signal power line, the response requires railway staff to go to each site on the line to investigate the trouble and provide corrective or temporary measures to restore service. This paper proposes to utilize existing infrastructure to control and indicate the signal power lines that includes sectionalization, remote stop/start of standby generators, and other function. Most signal power lines are concentrated at Centralized Traffic Control (CTC) points. These locations have connectivity to the central dispatching office via “Code Line” that can be expanded to incorporate a separate controls and indications for the signal power systems. Just as Dispatchers have software to help manage traffic on the railway; the new separate controls for the power system can be created to mimic safety protocols for system operation.
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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".