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Record W2015217673 · doi:10.1063/1.3499237

Fast reciprocating probe system on the EAST superconducting tokamak

2010· article· en· W2015217673 on OpenAlexaff
Wei Zhang, Jinming Chang, Baonian Wan, Guosheng Xu, C. J. Xiao, B. Li, Chongyang Xu, N. Yan, L. Wang, S.C. Liu, M. Jiang, P. Liu

Bibliographic record

VenueReview of Scientific Instruments · 2010
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsUniversity of Saskatchewan
FundersNational Natural Science Foundation of China
KeywordsReciprocating motionTokamakPlasmaPhysicsMaterials sciencePlasma diagnosticsMechanicsGas compressorNuclear physics

Abstract

fetched live from OpenAlex

A new fast reciprocating probe system (FRPS) has been built and installed on the outer midplane of the EAST tokamak to investigate the profiles of the boundary plasma parameters such as electron density and temperature. The system consists of a two-stage motion drive mechanism: slow motion and fast motion. The fast motion is powered by a servo motor, which drives the probe horizontally up to 50 cm to scan the edge region of the EAST tokamak. The maximum velocity achieved is 2 m/s. High velocity and flexible control of the fast motion are the remarkable features of this FRPS. A specially designed connector installed at the front end of the probe shaft makes it easy to install or replace the probe head on FRPS. During the latest experimental campaign in the spring of 2010, a probe head with seven tips, including two tips for a Mach probe, has been used. An example is given for simultaneous profile measurements of the plasma temperature, plasma density, and the plasma flow velocity.

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)0.001
metaresearch head score (Gemma)0.002
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: none
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.029
GPT teacher head0.279
Teacher spread0.250 · 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

Citations72
Published2010
Admission routes1
Has abstractyes

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