An examination of range effects when evaluating discomfort due to glare in Singaporean buildings
Bibliographic record
Abstract
This article discusses ratings of visual discomfort from glare across different buildings located in Singapore. These data were used to determine if range effects influence the vertical illuminance values for the same ratings of visual discomfort when the category rating procedure is used. The effect occurs when maxima and minima vertical illuminance (i.e. the range) vary across buildings. Our analyses showed that with a higher vertical illuminance range in a building, the mean vertical illuminance value for the same criterion of visual discomfort also increased. The results suggest that the effect caused by different ranges of measured vertical illuminance present across the buildings biased the ratings of visual discomfort. Although these effects may be unavoidable in some buildings that have vastly different levels of light, the data suggest that the overall range of vertical illuminance must be carefully evaluated when predicting visual discomfort. Matching these conditions may enable vertical illuminance to provide more reliable evaluations of discomfort due to glare.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 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".