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Record W4210866375 · doi:10.5539/jsd.v15n2p98

Civilization Needs Sustainable Energy – Fusion Breeding May Be Best

2022· article· en· W4210866375 on OpenAlexvenueno aff
Wallace M. Manheimer

Bibliographic record

VenueJournal of Sustainable Development · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicNuclear Issues and Defense
Canadian institutionsnot available
FundersNuclear Physics
KeywordsFissile materialFusion powerCivilizationNuclear powerNuclear fusionWind powerRenewable energyEnvironmental scienceHydroelectricityNatural resource economicsNuclear engineeringEnvironmental economicsBusinessGeographyEngineeringEconomicsArchaeologyNeutronEcologyNuclear physicsPhysicsBiologyElectrical engineering

Abstract

fetched live from OpenAlex

Civilization requires power. For a while it can get by with the power supplies we currently use, fossil fuel, nuclear fuel; and hydroelectric, solar and wind. Only the last 3 are sustainable. The first two will run out as some point, very likely well before the end of this century, especially if the less developed parts of the world come up to OECD standards. This paper makes the case that solar and wind are not up to the job, and neither is pure fusion, at least in this century. However, using fusion to breed fissile material for current nuclear reactors could play an important role well before century’s end. The requirements on a fusion device used as a breeder are considerably relaxed from the requirements for pure fusion. It is likely that an ITER type device, could be used for fusion breeding on a large scale. Fusion breeding can support nuclear fuel for civilization, at 30- 40 terawatts (TW), at least as far into the future as the dawn of civilization was in the past.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.024
Threshold uncertainty score0.081

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.005
Scholarly communication0.0050.007
Open science0.0000.004
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0240.012

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 head0.018
GPT teacher head0.263
Teacher spread0.245 · 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 designTheoretical or conceptual
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

Citations11
Published2022
Admission routes1
Has abstractyes

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