The Canadian Pacific DGRMS: The First Use of Deployable GRMS in a Production Mode
Bibliographic record
Abstract
The Deployable GRMS (DGRMS), which is capable of testing gage restraint at 50 mph, was originally developed for the FRA in 2004. Gage Restraint Measurement systems use a hydraulically loaded split axle to laterally push outward on each rail to expose gage restraint weaknesses. The DGRMS is the first system to utilize a deployable fifth axle instead of a running axle for this purpose. The FRA prototype system has been used in FRA research projects but not in a year-round daily production mode. Canadian Pacific Railway (CPR) procured the first production system that was installed on a box car and placed the system into service in February 2009. The first six months of service was used for equipment shakedown which resulted in a robust daily production system. The resultant system is being used year-round by CP, even on snow-covered rails. This paper describes the CP experience, the results of the test program, and new improvements in the technology.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 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".