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Record W2897026606 · doi:10.1063/1.5039335

Velocity-space sensitivity of time-of-flight neutron spectrometer at EAST in deuterium plasma

2018· article· en· W2897026606 on OpenAlexfundno aff
L. Ge, Zhimeng Hu, Y. M. Zhang, Jiaqi Sun, Xiaohui Yuan, Peng Xu, Z. J. Chen, T. F. Du, M. Nocente, G. Gorini, M. Tardocchi, Lisha Hu, Guoqiang Zhong, Baonian Wan, Xiaona Li, Tieshuan Fan

Bibliographic record

VenueReview of Scientific Instruments · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
FundersInstitute of Circulatory and Respiratory Health
KeywordsPhysicsNeutronSpectrometerNuclear physicsPlasma diagnosticsTime of flightNeutron spectroscopyDeuteriumPlasmaComputational physicsAtomic physicsOpticsNeutron scattering

Abstract

fetched live from OpenAlex

The Time-Of-Flight Enhanced Diagnostics (TOFED) neutron spectrometer with a double-ring structure has been installed at the Experimental Advanced Superconducting Tokamak (EAST) to perform advanced neutron emission spectroscopy diagnosis for deuterium plasma. In order to reduce the random coincidence from the background neutrons and gamma-rays, TOFED was moved outside the experimental hall and placed in the newly-built nuclear diagnostics laboratory in 2017. In this paper, the instrument-specific weight functions of TOFED are derived by taking the instrument response matrix and the radial line of sight in this new layout into consideration. The results show that the instrument is predominantly sensitive to counter-passing particles in the region where time-of-flights < 69.4 ns, while events at higher time-of-flights (corresponding lower neutron energies) are mostly representative of co-passing ions. The instrument-specific weight functions express the relationship between data in a given channel of the spectrum and the velocity space region that contributes to that. The results can be applied for energetic particle physics studies at EAST, in particular to compare data from different diagnostic techniques.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.404
Threshold uncertainty score0.958

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0430.000

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 head0.014
GPT teacher head0.263
Teacher spread0.249 · 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

Citations11
Published2018
Admission routes1
Has abstractyes

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