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Record W6947998937 · doi:10.4224/40003310

On the development of noise measurement guidelines for RPAS lighter than 150 kg

2023· report· en· W6947998937 on OpenAlexaffvenueabout

Bibliographic record

VenueNPARC · 2023
Typereport
Languageen
FieldMedicine
TopicBiological and pharmacological studies of plants
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsAnnoyanceNoise (video)Noise pollutionNoise controlNoise measurementBackground noiseAircraft noise

Abstract

fetched live from OpenAlex

The use of Remotely Piloted Aircraft Systems (RPAS) has experienced a significant increase in recent years. These systems are now being utilized for new purposes, such as package delivery, medical supply transportation, and urban videography. This has resulted in an uptick in their use, particularly in densely populated urban areas. However, for the use of RPAS to be sustainable, it is essential to maintain sound levels that are in line with or below the usual background levels of the region. It is worth noting that these levels can differ significantly between large city centers, suburbs, and rural areas. Studies funded by Transport Canada have revealed that noise pollution generated by RPAS may impede public acceptance, indicating that future noise regulations may need to consider social acceptability, taking into account not only safe noise levels, but also the annoyance and perception of noise by humans.

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)0.003
Version: codex-gemma-dda1882f352aValidation 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 score0.624
Threshold uncertainty score0.747

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.592
GPT teacher head0.447
Teacher spread0.145 · 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 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
Published2023
Admission routes3
Has abstractyes

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