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Record W1981204243 · doi:10.1121/1.4805561

The work of the Committee on Aviation Environmental Protection and the Development of International Noise Standards

2013· article· en· W1981204243 on OpenAlexaff
Jane Hupe

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2013
Typearticle
Languageen
FieldHealth Professions
TopicNoise Effects and Management
Canadian institutionsInternational Civil Aviation Organization
Fundersnot available
KeywordsCivil aviationMandateCertificationAviationAeronauticsWork (physics)NinthBusinessPolitical scienceEngineeringLaw

Abstract

fetched live from OpenAlex

Environmental Protection is one of the Strategic Objectives of ICAO. The overall aim is to minimize the adverse environmental effects of global civil aviation activity. One of the key objectives is to establish noise Standards to limit and reduce the number of people affected by aircraft noise. This mandate is carried out by the Committee on Aviation Environmental Protection (CAEP), which, as a technical committee of the ICAO Council, is a recognized international forum of environmental experts from both member and observer States, intergovernmental organizations, including airlines, aircraft and engine manufacturers, airports, environmental non-governmental organizations, and UN bodies. ICAO has set International Standards for aircraft noise certification since the 1970s, and the purpose of this talk is to describe the process of developing these Standards while providing some details on recent developments, including the key outcomes of three years’ worth of research leading up to the ninth meeting of the CAEP.

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)0.064
metaresearch head score (Gemma)0.066
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.064
Threshold uncertainty score0.336

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0640.066
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0070.004
Science and technology studies0.0050.007
Scholarly communication0.0140.005
Open science0.0050.004
Research integrity0.0110.024
Insufficient payload (model declined to judge)0.0070.007

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 head0.013
GPT teacher head0.295
Teacher spread0.283 · 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 designNot applicable
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
Published2013
Admission routes1
Has abstractyes

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Same venueThe Journal of the Acoustical Society of AmericaSame topicNoise Effects and ManagementFrench-language works237,207