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Record W2025658473 · doi:10.1080/00039890109604071

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

2001· article· en· W2025658473 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

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.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.917
Threshold uncertainty score0.418

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)0.0000.000

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