On the development of noise measurement guidelines for RPAS lighter than 150 kg
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.029 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.007 | 0.002 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.008 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".