MétaCan
Menu
Back to cohort
Record W4409500271 · doi:10.5006/c2024-20850

Advanced Crack Inspection Technology for Coke Drums

2024· article· en· W4409500271 on OpenAlexaff
Duane Serate, Gordon Cheuk Hei Ho, Simon Yuen, Yashar Behnamian

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnergy
TopicCoal and Coke Industries Research
Canadian institutionsSuncor Energy (Canada)
Fundersnot available
KeywordsCokeComputer scienceEngineeringForensic engineeringWaste management

Abstract

fetched live from OpenAlex

Abstract The typical operating cycles of coke drums create thermal stresses that eventually lead to fatigue cracks called ‘elephant skin’ (ES) in both the inside diameter (ID) and outside diameter (OD) of coke drums. Traditionally, these have been inspected through a multi-stage process from initial dye penetrant inspection, visual assessment of ES crack depth, baseline ultrasonic thickness (UT) gauging, exploratory grinding to chase crack tip/s of select locations, confirmatory dye penetrant inspection, and UT gauging to determine the remaining wall thickness, to calculate the crack depth. This traditional process is not only slow and a time-consuming chain of activities, but also leads to subjectivity in the crack depth assessment, and a challenge to coordinate different groups in a turn-around. An Eddy Current Array (ECA) inspection crawler was designed and built to solve these issues.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.925
Threshold uncertainty score0.872

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 head0.021
GPT teacher head0.316
Teacher spread0.295 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

Same topicCoal and Coke Industries ResearchFrench-language works237,207