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Record W2083574828 · doi:10.1115/ipc2004-0327

A Risk Assessment Model for Pipelines Exposed to Geohazards

2004· article· en· W2083574828 on OpenAlexaff
Fiona Esford, Michael J. Porter, K. Wayne Savigny, W. Kent Muhlbauer, C. R. B. Dunlop

Bibliographic record

Venue2004 International Pipeline Conference, Volumes 1, 2, and 3 · 2004
Typearticle
Languageen
FieldEngineering
TopicStructural Integrity and Reliability Analysis
Canadian institutionsBGC Engineering (Canada)
Fundersnot available
KeywordsPipeline transportRisk assessmentPipeline (software)TraverseTerrainRisk analysis (engineering)Risk managementEnvironmental scienceForensic engineeringGeologyEngineeringComputer scienceCivil engineeringMining engineeringPetroleum engineeringGeographyCartographyEnvironmental engineeringBusiness

Abstract

fetched live from OpenAlex

Transredes S.A. currently operates over 5,500 km of natural gas and liquids pipelines throughout Bolivia. These traverse geologically active terrain, subject to earthquakes, floods and landslides. Construction of these pipelines dates as far back as 1955, with some currently operating under conditions not foreseen at design. A quantitative risk assessment procedure was developed to rank the threats to the pipelines and target locations exposed to the highest level of risk. The objective was to implement a systematic means of prioritizing capital and maintenance activities based on risk management principles. The procedure was implemented on the OSSA-1 pipeline as part of a pilot study. This paper describes the OSSA-1 Pilot Project, with emphasis on how risk assessment procedures were customized to address the pipeline’s elevated exposure to ‘geohazards’.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.031
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0060.001

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.

Opus teacher head0.019
GPT teacher head0.272
Teacher spread0.253 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations21
Published2004
Admission routes1
Has abstractyes

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Same venue2004 International Pipeline Conference, Volumes 1, 2, and 3Same topicStructural Integrity and Reliability AnalysisFrench-language works237,207