MétaCan
Menu
Back to cohort
Record W2148521998 · doi:10.1115/ipc2002-27403

Evaluation of Pipeline Control Center Operator Skills Utilizing High Fidelity Pipeline Simulation Technology

2002· article· en· W2148521998 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

Venue4th International Pipeline Conference, Parts A and B · 2002
Typearticle
Languageen
FieldComputer Science
TopicDiverse Research and Applications
Canadian institutionsMetso (Canada)
Fundersnot available
KeywordsPipeline (software)Operator (biology)AutomationComputer scienceControl (management)FidelityPipeline transportHigh fidelitySimulationControl systemEngineeringOperating systemMechanical engineeringArtificial intelligenceTelecommunicationsElectrical engineering

Abstract

fetched live from OpenAlex

The U.S. Department of Transportation Operator Qualification Rule requires pipeline Control Center Operators to be evaluated on their ability to perform “covered tasks”, and recognize / react to abnormal operating conditions. ChevronTexaco has chosen to utilize pipeline simulation technology as a skill evaluation tool for its Control Center Operators. Metso Automation was selected to provide the pipeline simulation-based evaluation system. This paper provides an overview of the pipeline simulation application system that was selected and implemented by ChevronTexaco.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.961
Threshold uncertainty score0.863

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0010.000
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 head0.058
GPT teacher head0.329
Teacher spread0.271 · 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