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Record W4376871881 · doi:10.1186/s12940-023-00987-8

Health consequences of exposure to aircraft contaminated air and fume events: a narrative review and medical protocol for the investigation of exposed aircrew and passengers

2023· review· en· W4376871881 on OpenAlexaff
Jonathan Burdon, Lygia Therese Budnik, Xaver Baur, G. Hageman, C. V. Howard, Jorge Roig, Leonie Coxon, Clement E. Furlong, David Gee, Tristan Loraine, Alvin V. Terry, John Midavaine, Hannes Petersen, Denis Bron, Colin L. Soskolne, Susan Michaelis

Bibliographic record

VenueEnvironmental Health · 2023
Typereview
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsUniversity of Alberta
FundersNational Institute of Environmental Health SciencesUniversitätsklinikum Jena
KeywordsAircrewEnvironmental scienceMedicineEnvironmental healthInhalationOccupational exposureAeronauticsEngineeringAnesthesia

Abstract

fetched live from OpenAlex

Thermally degraded engine oil and hydraulic fluid fumes contaminating aircraft cabin air conditioning systems have been well documented since the 1950s. Whilst organophosphates have been the main subject of interest, oil and hydraulic fumes in the air supply also contain ultrafine particles, numerous volatile organic hydrocarbons and thermally degraded products. We review the literature on the effects of fume events on aircrew health. Inhalation of these potentially toxic fumes is increasingly recognised to cause acute and long-term neurological, respiratory, cardiological and other symptoms. Cumulative exposure to regular small doses of toxic fumes is potentially damaging to health and may be exacerbated by a single higher-level exposure. Assessment is complex because of the limitations of considering the toxicity of individual substances in complex heated mixtures.There is a need for a systematic and consistent approach to diagnosis and treatment of persons who have been exposed to toxic fumes in aircraft cabins. The medical protocol presented in this paper has been written by internationally recognised experts and presents a consensus approach to the recognition, investigation and management of persons suffering from the toxic effects of inhaling thermally degraded engine oil and other fluids contaminating the air conditioning systems in aircraft, and includes actions and investigations for in-flight, immediately post-flight and late subsequent follow up.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.783
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.101
GPT teacher head0.413
Teacher spread0.312 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations32
Published2023
Admission routes1
Has abstractyes

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