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Record W2282250997 · doi:10.1063/1.4942419

Observation of 20–400 kHz fluctuations in the U-3M torsatron

2016· article· en· W2282250997 on OpenAlexaff
M. Dreval, Yu. V. Yakovenko, E. L. Sorokovoy, A.S. Slavnyj, R. Pavlichenko, A.E. Kulaga, N. V. Zamanov, Akio Hirose

Bibliographic record

VenuePhysics of Plasmas · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsPhysicsPlasmaAtomic physicsExcited stateElectronExcitationPlasma oscillationIonLow frequencyComputational physicsNuclear physics

Abstract

fetched live from OpenAlex

First observations of quasi-coherent fluctuations in the frequency range of 20–400 kHz in Alfvén-wave-heated plasmas of the U-3M torsatron are presented. The excitation conditions of these modes depend on the radio frequency antenna type and the plasma density, the appearance of the modes correlating with the presence of both suprathermal electrons and high-energy ions in the plasma, which supports our opinion that the modes are excited by energetic particles. Complicated evolution of the mode frequencies with abrupt changes at the instants of plasma confinement transitions is observed at the initial stage of each discharge. The frequencies become stable at the stage of the plasma current flattop. Raw estimates show that toroidicity-induced Alfvén eigenmodes could be responsible for the 150–400 kHz fluctuations. Low-frequency 20–70 kHz bursts are observed during plasma confinement transitions. The poloidal mode number of one of these bursts with the frequency of 20 kHz burst was determined to be m = 2. This mode rotated in the electron diamagnetic rotation direction with a frequency lower than the geodesic acoustic mode frequency and can be identified as a drift-sound-type mode.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.461
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.027
GPT teacher head0.271
Teacher spread0.244 · 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 designBench or experimental
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

Citations6
Published2016
Admission routes1
Has abstractyes

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