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Record W1898809977 · doi:10.2172/968196

Western Renewable Energy Zones, Phase 1: QRA Identification Technical Report

2009· report· en· W1898809977 on OpenAlexafffund
R. Pletka, John A. Finn

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEnergy
TopicGlobal Energy and Sustainability Research
Canadian institutionsGovernment of Alberta
FundersAgriculture and Agri-Food CanadaGovernment of AlbertaU.S. Department of Energy
KeywordsRenewable energyResource (disambiguation)Identification (biology)Operations researchProcess (computing)Computer scienceEnvironmental economicsEnvironmental resource managementTelecommunicationsGeographyEnvironmental scienceEngineeringEconomicsElectrical engineeringEcology

Abstract

fetched live from OpenAlex

This report describes the Western Renewable Energy Zones (WREZ) Initiative Phase 1 Qualified Resource Area identification process, including the identification and economic analysis of Qualified Resource Areas (QRAs) and 'non-REZ' resources. These data and analyses will assist the Western US in its renewable energy transmission planning goals. The economic analysis in this report produced the input data for the WREZ Generation and Transmission model, which is a screening-level model to determine the optimal routing for and cost of delivering renewable energy from QRAs to load centers throughout the Western Interconnection. In June 2009, the Western Governors' Association accepted the Western Governors' Association WREZ Phase 1 Report in which the QRAs were mapped and the entire WREZ Phase 1 process was explained in general. That same month the Lawrence Berkeley National Laboratory released the WREZ Generation and Transmission Model (GTM), which was also developed by Black & Veatch. This report details the assumptions and methodologies that were used to produce the maps and resource analyses in the WGA report as well as the economic data used by the WREZ GTM. This report also provides the results of the non-REZ resource analysis for the first time in the WREZ initiative.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
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 score0.416
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.035
GPT teacher head0.360
Teacher spread0.325 · 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.

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

Citations20
Published2009
Admission routes2
Has abstractyes

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