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Record W2165019986 · doi:10.1177/1477153507081560

Individual control of electric lighting in a daylit space

2008· article· en· W2165019986 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 · 2008
Typearticle
Languageen
FieldEngineering
TopicBuilding Energy and Comfort Optimization
Canadian institutionsNational Research Council Canada
FundersLawrence Berkeley National Laboratory
KeywordsDimmerIlluminanceElectric lightDaylightLuminanceGLAREDaylightingComputer scienceDigital signageSmart lightingOpticsComputer graphics (images)Computer visionSimulationEngineeringElectrical engineeringPhysicsArchitectural engineeringMaterials scienceMultimedia

Abstract

fetched live from OpenAlex

Participants (N=40) occupied a glare-free, daylit office laboratory for 1 day, and were prompted every 30 min to use dimming control over electric lighting to choose their preferred light level. Illuminances and luminances were recorded before and after each control opportunity; luminance maps were generated using a calibrated, high-dynamic range digital camera. Although there was a wide variation in chosen light levels between individuals, results showed a significant negative correlation between prevailing desktop illuminance and change in dimmer setting. This indicates that, from the perspective of occupants, daylight does displace electric lighting. Surprisingly, we did not find any luminance-based measure that was as good a predictor of participant dimmer choice as illuminance measured on the desktop. On average, manual dimming control in this situation reduced energy use for lighting by 25% compared to a fixed system delivering 500lx of electric lighting on the desktop.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.470
Threshold uncertainty score0.487

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.022
GPT teacher head0.264
Teacher spread0.242 · 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