MétaCan
Menu
Back to cohort
Record W6943611036 · doi:10.1582/leuros.2010.06.03002

Demand-responsive lighting: a field study

2010· article· en· W6943611036 on OpenAlexfundvenueno aff

Bibliographic record

VenueNPARC · 2010
Typearticle
Languageen
FieldEngineering
TopicSmart Grid Energy Management
Canadian institutionsnot available
FundersNatural Resources CanadaNational Research Council CanadaPublic Works and Government Services CanadaElectric Power Research Institute
KeywordsElectricityElectric fieldElectric shockField (mathematics)Stress (linguistics)

Abstract

fetched live from OpenAlex

This research investigated the tolerance of office workers for decreased illumination levels. The purpose was to assess the dimming that could be tolerated to reduce electricity demand during periods of grid stress without major inconvenience to workers. Participants (N=33) in an office laboratory were exposed to an initial baseline electric lighting level of 400 lx on their desktops. The electric lighting was dimmed smoothly over 10 seconds. During the dim, and for 30 seconds afterwards, the participants performed a computer-based proofreading task. The participants indicated if they had noticed the change, and whether the lighting conditions were acceptable. This was repeated over multiple trials, with dimming from 0 to 80%, and with or without daylight.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.005
GPT teacher head0.209
Teacher spread0.203 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2010
Admission routes2
Has abstractyes

Explore more

Same venueNPARCSame topicSmart Grid Energy ManagementFrench-language works237,207