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Record W2044243023 · doi:10.1115/ipc2002-27296

Girth Welding of X100 Pipeline Steels

2002· article· en· W2044243023 on OpenAlexaff
Mark G. Hudson, S. A. Blackman, John Hammond, David V. Dorling

Bibliographic record

Venue4th International Pipeline Conference, Parts A and B · 2002
Typearticle
Languageen
FieldEngineering
TopicWelding Techniques and Residual Stresses
Canadian institutionsTransCanada (Canada)
Fundersnot available
KeywordsWeldingWeldabilityGirth (graph theory)Pipeline (software)MetallurgyMaterials scienceToughnessGas metal arc weldingArc weldingMechanical engineeringEngineeringMathematics

Abstract

fetched live from OpenAlex

Girth welding trials involving pipes of minimum proof strength 690 MPa (X100) from several linepipe manufacturers have been conducted. Welding consumable selections for the trials were based on background data generated at Cranfield University coupled with potential weld metal mechanical property requirements thought necessary for the implementation of X100 pipeline steels. Mechanised pulsed gas metal arc welding (PGMAW) and semi-automatic/ manual welding procedures were used to generate mechanical property data of mainline girth welds, tie-ins and repairs using equipment and procedures as close to current field practice as possible. The trials showed no detrimental weldability issues for the X100 steels examined. Testing comprised tensile, toughness (CVN and CTOD), hardness, side bend and nick break data generation, using pipeline welding specifications where possible.

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 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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.507
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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.031
GPT teacher head0.243
Teacher spread0.212 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations7
Published2002
Admission routes1
Has abstractyes

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