Canadian main track derailment trends, 2001 to 2014
Bibliographic record
Abstract
The Transportation Safety Board of Canada (TSB) maintains the Rail Occurrence Database System (RODS). This database contains information on all types of rail occurrences including derailments that must be reported by all Canadian railway operators. This paper analyzes the derailments that occurred on Canadian main track network between 2001 and 2014. The results from the analysis show that between 2001 and 2014 there was an overall decreasing trend in the number and intensity of main track derailments, derailments involving dangerous goods cars, and the number of derailments resulting in the release of dangerous goods. The RODS data was further analyzed to evaluate the frequency of the differing causes of derailments and the severity of the resulting incidents. The most common and severe derailment causes resulted from rail breaks, track geometry, and environmental conditions. Derailment velocity was also found to have an impact on the severity, with higher velocities resulting in a greater number of derailed rolling stock.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.009 | 0.015 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".