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Record W7010484594

Imagining the future of office lighting: smart, sustainable, solid-state

2013· article· en· W7010484594 on OpenAlexfundvenueaboutno aff

Bibliographic record

VenueNPARC · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicImpact of Light on Environment and Health
Canadian institutionsnot available
FundersOffice of Energy EfficiencyPublic Works and Government Services CanadaUniversity of Essex
KeywordsSmart lightingDaylightDaylightingTrack (disk drive)Energy (signal processing)WattOccupancy
DOInot available

Abstract

fetched live from OpenAlex

This is a time of revolutionary change in the lighting industry. Solid-state lighting (SSL) systems are on track to achieve lighting efficiencies for general lighting in excess of 150 lumens per watt (lm/W) in the not-too-distant future (see http://www1.eere.energy.gov/buildings/ssl/). This is double the typical performance of the ubiquitous linear fluorescent systems in use today. The total system performance could be further improved by the addition of smart controls, which include occupancy sensing and daylight harvesting, among other features. These controls are easier to implement with SSL systems because of SSL’s digital nature. Interestingly, SSL systems also offer other new functions for interior lighting that have yet to be fully explored. Having started in 2008 to consider what these new functions might be, and how they might be used, our team at the National Research Council of Canada is convinced that further development of these concepts will lead to greater energy savings for lighting, faster adoption of SSL lighting technologies, and improved lighting quality. This summary shows what we think in 2012 that the future will hold

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.183
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0100.001

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 head0.006
GPT teacher head0.225
Teacher spread0.220 · 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; both teacher heads agree on what is shown here.

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

Citations1
Published2013
Admission routes3
Has abstractyes

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