MétaCan
Menu
Back to cohort
Record W2536410470 · doi:10.1115/ipc2000-194

A New Multi-Level Assessment Procedure for Corroded Line Pipe

2000· article· en· W2536410470 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicStructural Integrity and Reliability Analysis
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsFailure assessmentCorrosionStructural engineeringUltimate tensile strengthLine (geometry)Finite element methodComputer scienceStress (linguistics)Materials scienceQuantitative assessmentReliability engineeringEngineeringComposite materialMathematicsGeometry

Abstract

fetched live from OpenAlex

A new assessment method to predict the failure pressure of corrosion defects in line pipe has been developed. Comparison to an experimental database shows that this new assessment procedure has advantages over existing techniques. The implementation of this method is proposed in a multi-level assessment procedure. The assessment levels are organized in terms of increasing complexity, with Level I being a lower bound solution and requiring only the maximum defect depth. The new assessment method requires detailed corrosion geometry measurements and is proposed as a Level II. Three dimensional elastic-plastic finite element analysis is proposed for the Level III. These methods assume the true stress-strain curve of the material is known, which can be determined from uniaxial tensile tests. When these material properties are unknown, the currently accepted codes are suggested for defect evaluation.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.617
Threshold uncertainty score0.997

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)0.0040.000

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 head0.034
GPT teacher head0.290
Teacher spread0.256 · 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