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Record W4200409202 · doi:10.1177/14771535211047220

An examination of range effects when evaluating discomfort due to glare in Singaporean buildings

2021· article· en· W4200409202 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueLighting Research & Technology · 2021
Typearticle
Languageen
FieldEngineering
TopicBuilding Energy and Comfort Optimization
Canadian institutionsUniversity of Toronto
FundersNational Research Foundation
KeywordsIlluminanceGLARERange (aeronautics)Matching (statistics)MathematicsOptometryEnvironmental scienceSimulationOpticsComputer scienceStatisticsEngineeringMedicinePhysicsMaterials science

Abstract

fetched live from OpenAlex

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.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.376
Threshold uncertainty score0.559

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.024
GPT teacher head0.327
Teacher spread0.303 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it