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Record W3097573591 · doi:10.1080/14786451.2020.1837132

Transitions towards energy-efficient appliances in urban households of Gujarat state, India

2020· article· en· W3097573591 on OpenAlexaboutno aff
Amit Garg, Jyoti Maheshwari, Debdatta Mukherjee

Bibliographic record

VenueInternational Journal of Sustainable Energy · 2020
Typearticle
Languageen
FieldEngineering
TopicBuilding Energy and Comfort Optimization
Canadian institutionsnot available
FundersBundesministerium für Umwelt, Naturschutz und Reaktorsicherheit
KeywordsElectricityAgricultural economicsAir conditioningCeiling (cloud)Quarter (Canadian coin)Energy consumptionEnvironmental scienceEnvironmental engineeringToxicologyGeographyEngineeringEconomicsMeteorologyElectrical engineering

Abstract

fetched live from OpenAlex

Residential sector accounted for 24% of the total electricity consumption in India during 2009–10 and has almost remained around one-quarter over the last decade. A total of 163 same urban households were surveyed in 2018 to ascertain the change in penetration and use of energy-efficient (EE) appliances therein over 2010–18. There was a significant increase in their penetration across each enduse category with main changes being in air conditioners (ACs) (47%) and LED lights (over 38 times) over 2010–18. The weighted average relative electricity consumption decreased from 0.89 to 0.44 for ACs (1.5TR), 0.42 to 0.23 for lighting lamps, 0.95 to 0.54 for tubelights, 0.98 to 0.68 for refrigerators, and 0.94 to 0.69 for TVs, indicating the lowering of average energy consumption due to EE appliances. The annual electricity savings at household level were found statistically significant for transitions to EE ACs and ceiling fans.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.557
Threshold uncertainty score0.479

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)0.0000.000

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 head0.006
GPT teacher head0.198
Teacher spread0.191 · 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 designSimulation or modeling
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

Citations8
Published2020
Admission routes1
Has abstractyes

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