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Record W2019282944 · doi:10.1088/1009-0630/17/3/03

Results of ICRF Heating Experiments from the EAST 2010 Campaign

2015· article· en· W2019282944 on OpenAlexfundno aff
Zhixiong He, Xinjun Zhang, Yanping Zhao, ICRH Team EAST

Bibliographic record

VenuePlasma Science and Technology · 2015
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
FundersInstitute of Circulatory and Respiratory HealthJapan Society for the Promotion of ScienceNational Natural Science Foundation of ChinaIsrael Cancer Research Fund
KeywordsEnvironmental scienceNuclear engineeringEngineering

Abstract

fetched live from OpenAlex

Radio frequency (RF) plasma heating in ion cyclotron range of frequencies (ICRF) was successfully performed on the Experimental Advanced Superconducting Tokamak (EAST). This is mainly because lithium wall conditioning was routinely used to reduce both impurity and hydrogen (H) recycling and to improve the ICRF power absorption. Mainly ICRF heating of the H minority regime at 27 MHz has been applied in deuterium plasmas. The ion cyclotron resonance heating (ICRH) is found to depend strongly on plasma preheating. The ICRH efficiency can be much improved in conjunction with the lower hybrid wave (LHW). Effective ion and electron heating was observed with the H minority heating mode. The increase of the stored energy reached 30 kJ in L-mode plasma by using the ICRF power of 1.0 MW alone when the H cyclotron resonance layer was at plasma center.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.033
GPT teacher head0.281
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations5
Published2015
Admission routes1
Has abstractyes

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