Traffic noise and sleep quality among aging adults - pilot experiment and data
Bibliographic record
Abstract
Indoor environmental quality is directly related to people's health and well-being. Noise exposure, for example, is a known cause of sleep disturbance and a risk factor for the development of cardiovascular disease. As people age, they are likely to become more sensitive to environmental conditions, yet most studies and guidance are based on research with young, working-age adults. As part of a broader project focused on establishing guidance for suitable interior conditions for adults as they age, the National Research Council of Canada in partnership with the National Institute of Advanced Industrial Science and Technology of Japan are jointly investigating the effects of traffic noise on the sleep quality of older adults. A pilot study has been developed in a quasi-controlled setup, where pre-recorded traffic noises modeled for two different façade performance levels were played during participants' sleep. Sleep quality was assessed using sleep data from wearable devices and self-reported sleep quality. The methods are described and preliminary findings from this experiment are presented, offering valuable insights and guiding the next phases of this research.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".