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Continuing Successful Low Energy Nuclear Fusion Reaction Experiments

2025· article· W7116854411 on OpenAlexaff
Dimiter Alexandrov, Yordan Paunov, Todor Malchev, D. N. Gospodinova, Milena Lazarova

Bibliographic record

Venuenot available
Typearticle
Language
FieldEarth and Planetary Sciences
TopicCold Fusion and Nuclear Reactions
Canadian institutionsLakehead University
FundersTechnical University of Sofia
KeywordsCold fusionNuclear reactionHeliumFusionLow energyEnergy (signal processing)Fusion power

Abstract

fetched live from OpenAlex

This paper builds on the continuous successful experiments of Low Energy Nuclear Reaction in solids in the Lakehead University’s Semiconductor Research Laboratory. In previous experiments excess heat generation, helium release and correlation between the two have been reported. The current paper aims to investigate the optimal temperature for deuterium-constantan interaction and lead to an increased reaction time and higher generated heat. Three initial temperatures have been tested $-510^{\circ} \mathrm{C}, 527^{\circ} \mathrm{C}$ and $535^{\circ} \mathrm{C}$. Similar reaction patterns have been observed with the first two temperatures and prolonged reaction time with the $\mathbf{5 3 5}^{\circ} \mathrm{C}$ experiment. From this the conclusion was drawn that this is the temperature where there is most energy release. The massspectroscopic analysis of the gases in the experiments confirms the nuclear origin of the released energy.

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), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.898
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0550.001

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 head0.008
GPT teacher head0.226
Teacher spread0.218 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations0
Published2025
Admission routes1
Has abstractyes

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