Current low frequency noise (LFN) assessment guidelines and their use in environmental noise impact assessment
Bibliographic record
Abstract
The Nature of Low Frequency N o ise -Discussed herein are current low frequency noise (LFN) noise assessment rating schemes, and key issues.LFN is not clearly defined, but generally covers noise in frequencies below 100 to 150 Hz.Infrasound (i.e., sub 20 Hz) is not usually audible but may still produce impacts through perceptibility.Infrasound LFN can produce resonances in human organs and tissues.(Berglmid ef al, 1996).One feels the noise as pressure sensations (DFRA, 2001).LFN can also rattle windows, dishes, etc. through sympathetic resonances, increasing annoyance (Bergland).Thus, LFN rating schemes typically go as low as 10 to 16 Hz.Typical rural sound environments have few man-made noise sources (e.g., traffic and industrial noise) and generally have "flat" frequency spectra.In urban environments, significant levels of ambient low frequency noise exist blit are generally less perceptible than in remote areas, due to masking by higher frequency noise within the "urban hum".LFN may be acceptable outdoors, particularly in urban environs.Indoors, building envelopes readily transmit LFN while higher frequency noises are blocked.This removes the masking effect of the high frequency noise, and can therefore increase the noticeability and related annoyance associated with the LFN portion of the spectrum.Closing the windows to block LFN noise only makes the problem worse.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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 teacher head, 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".