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Record W4224290555 · doi:10.1201/9781003277484-13

The Growth of the Indian Power Sector: Pre- and Post-Independence

2022· book-chapter· en· W4224290555 on OpenAlexaboutno aff
Shuvam Sahay, N. Kumar

Bibliographic record

VenueApple Academic Press eBooks · 2022
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicEnergy and Environment Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsPer capitaDistribution (mathematics)Independence (probability theory)Consumption (sociology)Renewable energyChinaProduction (economics)Development economicsElectricity generationNameplate capacityElectricityEconomicsEconomic growthPower (physics)EconomyGeographyEngineeringSocial sciencePopulationSociologyMacroeconomicsElectrical engineering

Abstract

fetched live from OpenAlex

Electricity played an essential role in the development and progress of the nations. The Indian power sector is one of the most variegated in the world. This chapter describes the growth of the Indian Power Sector from 1879 to till this date. It highlights the progress in generation, transmission, and distribution sector in terms of installed capacity, per capita consumption, losses, and actual generation. This chapter also presents comparison with some top countries like China, Japan, the USA, Brazil, Canada, and Germany in terms of energy production, energy consumption and transmission and distribution lose for showing the status of our country in the energy sector. This chapter also presents the scenario of energy production through renewable in India by comparing with other top countries of the world. Through this chapter, the authors want to present a picture in the minds of readers so that readers are able to know the progress and status of our Indian power sector and their shortcoming.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.021
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.006
Science and technology studies0.0010.002
Scholarly communication0.0050.002
Open science0.0010.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0070.003

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 head0.202
Teacher spread0.192 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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