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Record W2081744195 · doi:10.1117/12.639718

Solid state lighting for the developing world: the only solution

2005· article· en· W2081744195 on OpenAlexaff
Rudolfo Peon, Ganesh Doluweera, Inna Platonova, Dave Irvine-Halliday, Gregor Irvine-Halliday

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicEnergy and Environment Impacts
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsElectricitySolid-state lightingWork (physics)TelecommunicationsLED lampState (computer science)Architectural engineeringBusinessComputer scienceEngineeringLight-emitting diodeElectrical engineering

Abstract

fetched live from OpenAlex

Approximately two billion people, one third of humanity still has no access to electricity, and thus relies on fuel-based lighting, a dangerous alternative of last resort that is unhealthy, expensive, and offers very poor levels of illumination. This lack of light makes it difficult to perform most evening activities including studies by children and adults alike and therefore represents a significant barrier to human development. Over the past five years The Light Up The World Foundation (LUTW) has pioneered the use of the white light emitting diode (WLED) as an alternative home lighting solution, bringing clean, affordable light to thousands of non-electrified homes around the world. The information presented herein is intended to increase awareness of the enormous potential possessed by this emergent technology, "Solid State Lighting" (SSL), to improve the quality of life of millions of people around the world. The feasibility of its implementation is demonstrated with results from comprehensive field experience and laboratory research work. The mutual economic, social and environmental benefits for both stakeholders and SSL suppliers are discussed. Strategies conducive to the dissemination of this technology throughout the developing world are also presented.

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)0.001
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 score0.349
Threshold uncertainty score0.655

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.012
GPT teacher head0.238
Teacher spread0.226 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations43
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIESame topicEnergy and Environment ImpactsFrench-language works237,207