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Record W2001875020 · doi:10.1115/ipc2004-0272

Analysis of Ruptures and Trends on Major Canadian Pipeline Systems

2004· article· en· W2001875020 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

Venue2004 International Pipeline Conference, Volumes 1, 2, and 3 · 2004
Typearticle
Languageen
FieldEngineering
TopicStructural Integrity and Reliability Analysis
Canadian institutionsCanada Energy Regulator
Fundersnot available
KeywordsPipeline transportForensic engineeringPipeline (software)Psychological interventionCorrosionEngineeringEnvironmental scienceMedicineEnvironmental engineeringMetallurgyMaterials science

Abstract

fetched live from OpenAlex

The number of ruptures per year is one of the National Energy Board’s (the Board) measures of safety performance of the federally regulated oil and gas pipelines. This measure was examined and analyzed over twenty, ten, and five years with respect to the rupture causes, ignitions, fatalities, injuries, pipeline age, in-line inspections, and the Board’s safety interventions. There were forty-six ruptures over the twenty-year period, twenty-three over the ten-year period, and seven over the five-year period (Ref. 1 and 2) on the 43,000 km of the regulated pipelines. The average time from the pipeline installation to the time of rupture for the time-dependent rupture mechanisms is twenty-eight years. There were three fatalities and fourteen injuries caused by the ruptures of the federally regulated pipelines over the past twenty years. Ruptures associated with fires of the gas and high vapour pressure pipelines caused most of the fatalities and injuries. The dominant rupture causes are external corrosion, stress corrosion cracking, and third-party damage in this order of magnitude. The pipelines that ruptured during the last five years were internally inspected. The in-line inspection tools could not properly detect the defects that caused the ruptures. Regulatory interventions, such as public inquires, Board Orders, and regulatory requirements, have reduced the number of ruptures due to the targeted cause. The number of ruptures and safety consequences associated with them have decreased over the last ten years.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.163
Threshold uncertainty score0.951

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.010
GPT teacher head0.230
Teacher spread0.220 · 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