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Record W1973334429 · doi:10.1063/1.1290281

Locked modes in two reversed-field pinch devices of different size and shell system

2000· article· en· W1973334429 on OpenAlexaboutno aff
J-A Malmberg, P. R. Brunsell, Yuji Yagi, H. Koguchi

Bibliographic record

VenuePhysics of Plasmas · 2000
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsPhysicsReversed field pinchPlasmaPinchToroidAmplitudeAtomic physicsMagnetic fieldScalingPhase (matter)Computational physicsCondensed matter physicsQuantum electrodynamicsNuclear physicsQuantum mechanics

Abstract

fetched live from OpenAlex

The behavior of locked modes in two reversed-field pinch devices, the Toroidal Pinch Experiment (TPE-RX) [Y. Yagi et al., Plasma Phys. Control. Fusion 41, 2552 (1999)] and Extrap T2 [J. R. Drake et al., in Plasma Physics and Controlled Nuclear Fusion Research 1996, Montreal (International Atomic Energy Agency, Vienna, 1996), Vol. 2, p. 193] is analyzed and compared. The main characteristics of the locked mode are qualitatively similar. The toroidal distribution of the mode locking shows that field errors play a role in both devices. The probability of phase locking is found to increase with increasing magnetic fluctuation levels in both machines. Furthermore, the probability of phase locking increases with plasma current in TPE-RX despite the fact that the magnetic fluctuation levels decrease. A comparison with computations using a theoretical model estimating the critical mode amplitude for locking [R. Fitzpatrick et al., Phys. Plasmas 6, 3878 (1999)] shows a good correlation with experimental results in TPE-RX. In Extrap T2, the magnetic fluctuations scale weakly with both plasma current and electron densities. This is also reflected in the weak scaling of the magnetic fluctuation levels with the Lundquist number (∼S−0.06). In TPE-RX, the corresponding scaling is ∼S−0.18.

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 score0.620
Threshold uncertainty score0.994

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)0.0070.000

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 head0.009
GPT teacher head0.254
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 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

Citations20
Published2000
Admission routes1
Has abstractyes

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