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Record W2168770873 · doi:10.1109/wnwec.2009.5335775

Wind energy resources exploitation and large-scale, non-grid-connection wind-powered industrial bases, construction in China Northwest Territories

2009· article· en· W2168770873 on OpenAlexaboutno aff
Haiyan Liu, Yanli Kuai, Chuanglin Fang, Maoxun Li

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicWind Energy Research and Development
Canadian institutionsnot available
Fundersnot available
KeywordsWind powerGrid connectionNameplate capacityEnvironmental scienceGridRenewable energyCivil engineeringChinaMeteorologyElectricity generationEngineeringPower (physics)Electrical engineeringGeography

Abstract

fetched live from OpenAlex

Northwest Territories in China is very rich in wind energy resources and has huge potential in development wind power, million kilowatts of wind power base is in planning and preparation, the wind power industry has entered a rapid and important development period. According to incomplete statistics, 2007, the wind farm of Built and under-construction are 23, the total installed capacity reached 1.4009 million kilowatts, and it is projected that the wind power installed capacity will reach 19.6892 million kilowatts in 2020, accounting for 38 percent of installed capacity of China. the paper reviewed the wind energy resources development research progress, analysis and assess the Northwest resources development and utilization of wind energy; identify the existing problems in the Northwest development of wind power industry; proposed wind energy resources development and the principle of non-grid wind power development goals In Northwest, using this as guide, integrate two national non-network and wind power and high energy-consuming non - Carbon-type industrial base: northern in Xinjiang net non-wind power and high energy-consuming industrial base and Jiuquan in Gansu net non-wind power and high energy-consuming industrial base, And layout ideas for each industrial base, put forward corresponding policies and measures of wind energy development and non-grid wind power industry base construction in final.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.398
Threshold uncertainty score0.703

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 head0.007
GPT teacher head0.200
Teacher spread0.193 · 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 designObservational
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

Citations5
Published2009
Admission routes1
Has abstractyes

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