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Record W2514378967

Investigation of Aircrew Noise Exposure Onboard the NRC Dassault Falcon Aircraft Through Flight Testing

2016· article· en· W2514378967 on OpenAlexaffvenueabout
Andrew Price, Sebastian Ghinet, Viresh Wickramasinghe

Bibliographic record

VenueCanadian acoustics · 2016
Typearticle
Languageen
FieldHealth Professions
TopicNoise Effects and Management
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsAircrewAeronauticsNoise (video)Octave bandEnvironmental scienceEngineeringAerospace engineeringOctave (electronics)AcousticsComputer sciencePhysics
DOInot available

Abstract

fetched live from OpenAlex

The NRC Dassault Falcon 20 is a small business jet operated by the NRC Flight Research Laboratory as a customizable research and experimental facility. As such, the NRC Falcon flies in a variety of cabin configurations and flight conditions including parabolas for microgravity. In-flight cabin noise measurements were performed on the NRC Falcon throughout a number of representative flight conditions. The data was analyzed in 1/3rd octave bands in accordance with ISO 5129 and evaluated in accordance with the Canadian Aviation Occupational Health and Safety Regulations. It was determined that all aircrew equipped with properly fitted hearing protection will not be overexposed to noise while onboard the NRC Falcon. The most severe noise exposure was experienced at the rear of the cabin near the engines during level flight while accelerating to 300 KIAS. While not equipped with properly fitted hearing protection, an occupant will reach the maximum allowed noise dose in a cumulated 9 minutes and 36 seconds under these conditions.

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 score0.024
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.068
GPT teacher head0.319
Teacher spread0.251 · 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

Citations0
Published2016
Admission routes3
Has abstractyes

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