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Record W4409500994 · doi:10.5006/c2024-20705

Use of AMPP SP 0113 for Methods Selection and Implementation of Pipeline Integrity Management

2024· article· en· W4409500994 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.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicStructural Integrity and Reliability Analysis
Canadian institutionsGibson Energy (Canada)
Fundersnot available
KeywordsPipeline (software)Computer scienceSelection (genetic algorithm)Operating systemArtificial intelligence

Abstract

fetched live from OpenAlex

Abstract This paper provides an overview of 2023 version of NACE SP 0113: Pipeline Integrity Management (PIM): Methods Selection and Implementation. This standard practice presents guidance to operators for selecting and implementing methods, technologies, or activities to manage pipeline integrity. The 2023 version describes a PIM program that addresses threats (including from corrosion and other risks): covers both metallic (carbon steel) and non-metallic pipelines; provides definitions of various PIM terms; lists documentation requirements; discusses pipeline types; explains stages of pipeline life cycle; includes typical threats and stages of their occurrence; explains mitigation of the threats; describes integrity assessment and management methods; describes procedures to select appropriate PIM methods; describes PIM program implementation using Key Performance Indicators (KPI) and describes the state of implementation of PIM program in various companies using KPI.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.865
Threshold uncertainty score0.212

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.040
GPT teacher head0.368
Teacher spread0.328 · 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