Evaluating the Potential Health Impact of Obtrusive Light: Application to Montréal, Canada
Bibliographic record
Abstract
This paper describes the use of a new obtrusive light module of the Illumina v2 model to estimate the light that may enter bedroom windows. We used as input to the model, 1- the sources’ flux and spectrum derived from the color images taken by astronauts from the international space station, 2- an association between source spectrum and angular emission, and 3- a per zone inventory of obstacles properties and lamp height. The model calculate the spectral irradiance incident to buildings’ windows taking into account for the orientation of the street. By using the color information from an ISS image, we can classify pixels as a function of their spectra. With the same image, it is also possible to determine the upward photopic radiance for each pixel. Both serve as inputs to the model to calculate the spectral irradiance on any window. By having the spectral irradiance, it is possible to determine the Melatonin Suppression Index and the photopic irradiance on the window. Such information can later be used to perform epidemiological studies. The new methodology is applied to the case of Montréal in Canada for a set of houses’ locations. The computations are made for 2013 (pre-LED era).
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 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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".