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Record W2031327648 · doi:10.1191/1365782803li064oa

Monitoring manual control of electric lighting and blinds

2003· article· en· W2031327648 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueLighting Research & Technology · 2003
Typearticle
Languageen
FieldEngineering
TopicBuilding Energy and Comfort Optimization
Canadian institutionsNational Research Council Canada
FundersNatural Resources Canada
KeywordsElectric lightClosing (real estate)Control (management)Computer scienceEngineeringSimulationArchitectural engineeringAutomotive engineeringArtificial intelligenceElectrical engineeringBusiness

Abstract

fetched live from OpenAlex

This paper reviews, validates and extends present knowledge of the degree and kind of manual control strategies of blinds and electric lighting systems that are used in private and two-person offices. A new monitoring setup was applied from March to December 2000 in 10 daylit offices in Germany that featured manually operated electric lighting and automatically controlled external venetian blinds with manual override. The data shows that individuals consistently followed the same control strategy for their electric lighting and blinds. Groups of individuals tended to activate their electric lighting according to Hunt’s probability function, although there was a large spread between individual control levels. All subjects used their blinds to avoid direct sunlight above 50 W/m 2 , and incoming solar gains above 50 klux (~450 W/m 2 ). They also were more willing to accept automatic blind opening than closing.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.375
Threshold uncertainty score0.441

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.015
GPT teacher head0.283
Teacher spread0.269 · 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