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Record W7009922100

Floatplane Source Noise Measurements : Summary of Measurements, Data and Analyses for the Cessna 182S Skylane and De Havilland Canada DHC-2 Beaver.

2012· other· en· W7009922100 on OpenAlexaboutno aff

Bibliographic record

VenueRosa P: A digital library for transportation research (United States Department of Transportation) · 2012
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsAviationNational parkNoise (video)Center (category theory)National standardAircraft noiseService (business)National Airspace System
DOInot available

Abstract

fetched live from OpenAlex

The U.S. Department of Transportation, John A. Volpe National Transportation Systems Center (Volpe Center), Environmental Measurement and Modeling Division, provides technical support to the Federal Aviation Administration (FAA), with the cooperation of the National Park Service (NPS), in the development of Air Tour Management Plans (ATMPs) for National Parks with commercial air tours. In September 2010, the Volpe Center measured source noise for two floatplane aircraft that have been identified as participating in commercial air tour operations over National Parks: Cessna 182S and De Havilland Canada DHC-2. This document describes the planning and execution of the noise study, overviews the data reduction procedures, and presents final data adjusted to standard conditions.\n

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)0.001
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.903
Threshold uncertainty score0.196

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.005
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.005

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 head0.133
GPT teacher head0.340
Teacher spread0.207 · 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 designBench or experimental
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
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueRosa P: A digital library for transportation research (United States Department of Transportation)French-language works237,207