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Record W2737936997 · doi:10.1139/cjce-2017-0076

Canadian main track derailment trends, 2001 to 2014

2017· article· en· W2737936997 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2017
Typearticle
Languageen
FieldEngineering
TopicRailway Engineering and Dynamics
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsDerailmentTrack (disk drive)Forensic engineeringStock (firearms)EngineeringTransport engineeringGeographyArchaeology

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.895
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.007
GPT teacher head0.187
Teacher spread0.180 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it