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Record W1998167068 · doi:10.1115/icone17-75949

Why Massive Nuclear Deployment is Essential

2009· article· en· W1998167068 on OpenAlexaff
Alistair I. Miller, Romney B. Duffey

Bibliographic record

VenueVolume 2: Structural Integrity; Safety and Security; Advanced Applications of Nuclear Technology; Balance of Plant for Nuclear Applications · 2009
Typearticle
Languageen
FieldEnergy
TopicGlobal Energy and Sustainability Research
Canadian institutionsAtomic Energy (Canada)
Fundersnot available
KeywordsPer capitaNatural resource economicsSoftware deploymentPopulationWind powerGlobal warmingClimate changeBusinessEnergy supplyGreenhouse gasEnvironmental economicsEnvironmental scienceEnvironmental resource managementEnergy (signal processing)EconomicsComputer scienceEngineering

Abstract

fetched live from OpenAlex

Avoiding CO2 emissions while meeting global energy needs is a far greater challenge than most commentators and governments appreciate. Even the Intergovernmental Panel on Climate Change has offered no scenario that would stabilize atmospheric levels. The capacity of the oceans to absorb CO2 is limited to about 40% of the level of emissions in 1990. Shared equitably among the present-day world population, per capita emissions of 35% of the current European average would only return the world to 100% of 1990 emission levels. Yet world population will probably grow by 25% by 2050 and, between 1990 and 2007, global emissions increased by 29%. Our current global trajectory is hurtling us toward ever-higher levels, perhaps even disaster. Consequently, near-zero-emitting sources are the only approaches to energy generation that should be deployed. Nuclear power, with its immense energy density, is the only available source that qualifies for widespread deployment. Existing alternative options are not and cannot effectively contribute (see e.g. MacKay, 2008). The weakness in wind is the need for back-up and supplementation, not so much from its short-term fickleness but its seasonal variability. Carbon capture and storage would have to achieve far higher levels of capture than currently seem feasible. Hydroelectricity has limited remaining potential as well as needing careful deployment to avoid collateral emissions. Aggressive conservation and efficiency measures reduce but do not solve the growth in energy demand and usage. Global economic downturns provide temporary relief but huge social political pain, and energy supply security concerns remain unresolved issue for many countries, even today. Of course nuclear alone would face an overwhelming challenge. We shall need to deploy massive improvements in the efficiency with which energy is used. Solar power in various forms has promise and could have a substantial role at lower latitudes in consistently sunny areas though photovoltaic electricity is still a high-cost option. Geothermal and various forms of ocean-derived energy have development potential. However, we argue that worldwide deployment of 5000 to 10 000 nuclear reactors by 2050 is the only clearly accessible pathway to CO2 stabilization that exists today. This will require extension of the resource beyond once-through cycles and so the deployment of advanced reactor types. But it is doable, it is affordable, and our planet must plan to accomplish this deployment.

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)0.006
metaresearch head score (Gemma)0.025
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.026
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.025
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.005
Scholarly communication0.0040.008
Open science0.0010.002
Research integrity0.0070.007
Insufficient payload (model declined to judge)0.0260.009

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 head0.005
GPT teacher head0.248
Teacher spread0.243 · 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
GenreCommentary

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
Published2009
Admission routes1
Has abstractyes

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