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Record W1500636658 · doi:10.2172/764567

Green Power Marketing in the United States: A Status Report (Fifth Edition)

2000· report· en· W1500636658 on OpenAlexaboutno aff
B. Swezey, Lori Bird

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEngineering
TopicICT Impact and Policies
Canadian institutionsnot available
Fundersnot available
KeywordsRenewable energyCompetition (biology)ElectricityElectric power industryQuarter (Canadian coin)Electric powerBusinessMarketingPower (physics)Electric energyElectricity marketElectricity generationEnvironmental economicsEconomicsIndustrial organizationEngineeringElectrical engineering

Abstract

fetched live from OpenAlex

For the first time in many decades, consumers are being given a choice of who supplies their electric power and how that power is generated. One of these choices is to support electricity generation from more environmentally beneficial energy sources. The term green power generally refers to electricity supplied from renewable energy sources. By some estimates, nearly one-quarter of all U.S. consumers will have the option to purchase green power by the year 2000, either from their regulated utility provider or in competitive markets. As competition spreads in the electric power industry, more consumers will have this choice. The purpose of this brief is to provide electric industry analysts with information on green power market trends. Descriptive information on green power marketing activities in competitive and regulated market settings is included.

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)0.001
metaresearch head score (Gemma)0.001
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.064
Threshold uncertainty score0.128

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.005
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0180.009

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 head0.018
GPT teacher head0.268
Teacher spread0.251 · 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

Citations52
Published2000
Admission routes1
Has abstractyes

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