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Record W2016935047 · doi:10.1115/2000-gt-0328

Water Mist Fire-Fighting System in the Marine LM2500 Gas Turbine Module

2000· article· en· W2016935047 on OpenAlex
Glenn McAndrews, Victor M. Gameiro, Tom Shirriff

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

VenueVolume 1: Aircraft Engine; Marine; Turbomachinery; Microturbines and Small Turbomachinery · 2000
Typearticle
Languageen
FieldEngineering
TopicCombustion and Detonation Processes
Canadian institutionsRoyal Canadian Navy
Fundersnot available
KeywordsMistEnclosureGas turbinesTurbineEnvironmental scienceMarine engineeringAeronauticsFire protectionFirefightingEngineeringComputer scienceAerospace engineeringMechanical engineeringMeteorologyElectrical engineeringCivil engineeringPhysicsGeography

Abstract

fetched live from OpenAlex

Gas turbine packagers and end users find themselves today faced with the problem of identifying optimal gas turbine enclosure fire-fighting systems in an era of evolving technology. Research over the last several years has identified water mist as one of the most promising candidates for marine gas turbine enclosures. This paper will discuss the background and implementation of such a system in a military marine gas turbine enclosure.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.545
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.005
GPT teacher head0.177
Teacher spread0.172 · 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