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Record W582005381 · doi:10.15173/esr.v23i1.3312

THREE INVESTMENT SCENARIOS FOR FUTURE NUCLEAR REACTORS IN EUROPE

2017· preprint· en· W582005381 on OpenAlexvenueno aff
Bianka Shoai Tehrani, Pascal da Costa

Bibliographic record

VenueEnergy Studies Review · 2017
Typepreprint
Languageen
FieldEngineering
TopicNuclear reactor physics and engineering
Canadian institutionsnot available
Fundersnot available
KeywordsNuclear powerInvestment (military)LiberalizationNuclear technologyBusinessElectricityClimate changeNatural resource economicsEconomicsEngineeringMarket economyPolitical sciencePolitics

Abstract

fetched live from OpenAlex

While nuclear power may experience a technological breakthrough in Europe with Generation IV nuclear reactors within a few decades (2040), several events and drivers could question this possibility, e.g. the Fukushima accident, climate issues and liberalization of the electricity market.This article analyzes how the conditions necessary for their industrial development from now up to 2040 can be either favorable or detrimental to future nuclear reactors compared with other technologies and according to four main investment drivers: 1) technical change, 2) policy, 3) market, and 4) power company drivers.Twenty-four scenarios have been identified through structural analysis, with only three proving to be favorable to the development of future nuclear reactors.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.617
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.040
GPT teacher head0.267
Teacher spread0.227 · 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
GenreReview

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
Published2017
Admission routes1
Has abstractyes

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