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Record W2092817663 · doi:10.1186/2193-2697-3-10

Policy analysis of China inland nuclear power plants’ plan changes: from suspension to expansion

2014· article· en· W2092817663 on OpenAlexaff
Jinxin Zhu, Gail Krantzberg

Bibliographic record

VenueENVIRONMENTAL SYSTEMS RESEARCH · 2014
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicNatural Resources and Economic Development
Canadian institutionsMcMaster UniversityUniversity of Regina
Fundersnot available
KeywordsNuclear powerChinaRestructuringNuclear power plantGovernment (linguistics)Nuclear energy policyPlan (archaeology)Public policyPoliticsEnvironmental planningBusinessNatural resource economicsEnvironmental protectionEnvironmental resource managementPolitical scienceEconomic growthEnvironmental scienceEconomicsGeographyFinanceEcology

Abstract

fetched live from OpenAlex

Background China's inland nuclear power plants plan has been suspended until 2015 since Fukushima disaster. The policy on inland nuclear power plants becomes uncertain. This paper provides an overview of inland nuclear power plants the safety grantee, economic power on diminishing disparities between Western China and Eastern China, efforts on environmental improvement with reforming of energy restructure and essential public participation. The paper further discusses the government’s current policy and successful experience from other countries. Results The paper gives the recommendations for promoting inland nuclear power plants’ expansion, making economy develop healthily, improving environment and introducing public hearing into the nuclear power development. Conclusions With proper political guiding, China could obtain significant benefits from expanding nuclear power plants from coast to inland.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.135
Threshold uncertainty score0.268

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.000

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 head0.039
GPT teacher head0.250
Teacher spread0.211 · 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 designQualitative
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

Citations3
Published2014
Admission routes1
Has abstractyes

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