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Record W2056550254 · doi:10.1121/1.4743133

Rotorcraft noise model (RNM) and acoustic repropagation technique (ART2) validation and application using CH-146 (Bell 412) measurement data

2000· article· en· W2056550254 on OpenAlexaboutno aff
Juliet Page, J. Micah Downing

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2000
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicUnderwater Acoustics Research
Canadian institutionsnot available
Fundersnot available
KeywordsNoise (video)StandardizationMicrophoneAcousticsConsistency (knowledge bases)Computer scienceBroadbandAerospace engineeringEngineeringPhysicsTelecommunicationsArtificial intelligence

Abstract

fetched live from OpenAlex

A series of acoustic measurements were conducted at Moose Jaw Canadian Forces Base, Saskatchewan, Canada in June, 1998 for obtaining detailed noise data on a large array of ground- and crane-based microphones for a CH-146 helicopter. The project, conducted by the North Atlantic Treaty Organization (NATO) Committee on the Challenges of Modern Society was to define test procedures and analysis methods for the standardization of a NATO rotorcraft noise database. Four independent microphone arrays were deployed by the USAF, NASA, RAF, and DERA. Data from the USAF and NASA arrays were used to validate the Rotorcraft Noise Model (RNM). USAF data were processed via an updated acoustic repropagation technique (ART2) to define the rotorcraft broadband sound hemispheres. The source noise was then propagated to the measurement locations using RNM. Agreement with the original USAF measurements demonstrated consistency of the ART/RNM process. Agreement with the independent NASA measurements provided validation of the RNM as a prediction tool.

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)0.002
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.864
Threshold uncertainty score0.303

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.053
GPT teacher head0.281
Teacher spread0.228 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreMethods

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

Citations1
Published2000
Admission routes1
Has abstractyes

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