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Record W2793519996 · doi:10.1787/6ad4d5e3-en

Leveraging the Smart Grid

2018· paratext· en· W2793519996 on OpenAlexafffund
Nicholas Rivers

Bibliographic record

VenueOECD environment working papers · 2018
Typeparatext
Languageen
FieldEngineering
TopicSmart Grid Energy Management
Canadian institutionsUniversity of Ottawa
FundersUniversity of Ottawa
KeywordsSmart gridElectricityConsumption (sociology)Environmental economicsDemand responseElectricity demandGridBusinessComputer scienceEconomicsEngineeringGeographyElectricity generationElectrical engineeringPower (physics)

Abstract

fetched live from OpenAlex

This report reviews the literature on the impact of real-time information provision on consumer decision-making. In addition, it describes the results of a study in which about 7000 households in Ontario, Canada were provided with in-home displays linked to smart meters that provided real-time feedback on electricity consumption. The results show that electricity consumption declines by about 3% as a result of information feedback, that the reduction in demand is sustained for at least five months, and that it is highly correlated with outdoor temperature.

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)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.019
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0060.009
Open science0.0010.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0190.007

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 head0.011
GPT teacher head0.173
Teacher spread0.162 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations9
Published2018
Admission routes2
Has abstractyes

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