Evaluating project-related noise impacts on sleep in environmental assessments: A proposal to apply decibel adjustments to nighttime noise events based on their time of occurrence over the sleep period time
Bibliographic record
Abstract
Health Canada is updating its Guidance for evaluating noise in environmental assessments. Current advice on sleep is drawn from the World Health Organization (WHO) which advises that average noise within the bedroom not exceed 30 dBA, and noise events not exceed 45 dB LAmax on more than 10–15 occasions. Both limits increase by 15 dB outdoors assuming partially opened windows. The WHO’s recommended outdoor nighttime annual average of 40 dBA is also used. Two situations commonly arise: (1) the outdoor annual average sound level is exceeded at baseline; or (2) the number of events during sleep exceeds 15, but are just below threshold. Under these situations, the estimated prevalence of high noise annoyance is applied to protect sleep because it includes a 10 dB nighttime penalty. However, this may not account for the variation in the acoustic threshold that has been observed throughout the sleep period. This paper presents two proposals: (1) apply a decibel adjustment to noise events occurring during periods where thresholds are known to be lower (i.e., the first hour and final 3 h) and/or (2) derive a rating level for estimating annoyance using an alternative nighttime adjustment that splits the night into distinct time periods.
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 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 | 0.070 | 0.084 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".