MétaCan
Menu
Back to cohort
Record W2025658473 · doi:10.1080/00039890109604071

Hydraulic Fluids and Jet Engine Oil: Pyrolysis and Aircraft Air Quality

2001· article· en· W2025658473 on OpenAlexaff
Chris van Netten, Victor C. M. Leung

Bibliographic record

VenueArchives of Environmental Health An International Journal · 2001
Typearticle
Languageen
FieldEngineering
TopicCombustion and Detonation Processes
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsHydraulic fluidEnvironmental scienceSmokePyrolysisJet fuelPyrolysis oilWaste managementHydraulic machineryEngineeringMechanical engineering

Abstract

fetched live from OpenAlex

Incidents of smoke in aircraft cabins often result from jet engine oil and/or hydraulic fluid that leaks into ventilation air, which can be subjected to temperatures that exceed 500 degrees C. Exposed flight-crew members have reported symptoms, including dizziness, nausea, disorientation, blurred vision, and tingling in the legs and arms. In this study, the authors investigated pyrolysis products of one jet engine oil and two hydraulic fluids at 525 degrees C. Engine oil was an important source of carbon monoxide. Volatile agents and organophosphate constituents were released from all the agents tested; however, the neurotoxin trimethyl propane phosphate was not found. The authors hypothesized that localized condensation of pyrolysis products in ventilation ducts, followed by mobilization when cabin heat demand was high, accounted for mid-flight incidents. The authors recommended that carbon monoxide data be logged continuously to capture levels during future incidents.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.011
GPT teacher head0.273
Teacher spread0.262 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

Citations53
Published2001
Admission routes1
Has abstractyes

Explore more

Same venueArchives of Environmental Health An International JournalSame topicCombustion and Detonation ProcessesFrench-language works237,207