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Record W1991626417 · doi:10.1063/1.3247902

Retarding field energy analyzer for the Saskatchewan Torus–Modified plasma boundary

2009· article· en· W1991626417 on OpenAlexaffabout
M. Dreval, D. Rohraff, C. Xiao, Akira Hirose

Bibliographic record

VenueReview of Scientific Instruments · 2009
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsUniversity of Saskatchewan
FundersNuclear Physics
KeywordsLangmuir probeElectron temperatureTokamakPlasmaIonPlasma diagnosticsMaterials scienceAtomic physicsSpectrum analyzerMagnetic fieldElectronTorusPhysicsOpticsNuclear physics

Abstract

fetched live from OpenAlex

The retarding field energy analyzer (RFA) is a simple and reliable diagnostic technique to measure the ion temperature in the scrape-off layer and edge of magnetic fusion devices. Design and operation features of a single-sided (facing the ion flow) RFA for ion temperature measurements in the Saskatchewan Torus-Modified (STOR-M) tokamak are described. Its compact size (21 x 15 x 20 mm3) allows RFA measurements without perturbing plasma significantly. Both ion and electron temperature have been measured by RFA in the STOR-M tokamak. A method is proposed to correct the effects of ion flow on the ion temperature using the simultaneously measured Mach number. The measured electron temperature is consistent with the previously reported Langmuir probe data. Abnormal behavior of the RFA has been observed in both ion and electron modes when RFA is inserted deep into the plasma.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.966
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0160.000

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 head0.018
GPT teacher head0.283
Teacher spread0.265 · 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 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

Citations33
Published2009
Admission routes2
Has abstractyes

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