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Record W3193434004 · doi:10.1088/1741-4326/ac189c

Observation of self-organized FRC formation in a collisional-merging experiment

2021· article· en· W3193434004 on OpenAlexaff
Tomohiko Asai, D. Kobayashi, T. Seki, Yasuaki Tamura, Tatsuhiro WATANABE, Naoto Sahara, Tsutomu Takahashi, Jordan Morelli, H. Gota, T. Roche, Richard Magee, Michl Binderbauer, T. Tajima, Michiaki Inomoto, Toshiki Takahashi

Bibliographic record

VenueNuclear Fusion · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsQueen's University
Fundersnot available
KeywordsToroidPhysicsPlasmoidMagnetic fieldField-reversed configurationPlasmaAtomic physicsMechanicsMagnetic confinement fusionNuclear physicsTokamakMagnetic reconnection

Abstract

fetched live from OpenAlex

Abstract Self-organized field-reversed configuration (FRC)-like formation was observed after the super-sonic/Alfvénic collisional merging of two FRCs in the FAT-CM device at Nihon University. In this experiment, two FRCs were generated initially in two separate field-reversed theta-pinch type formation regions. Those two formation regions are coaxially connected to opposite ends of a cylindrical confinement chamber. The formed FRCs are oppositely-translated and collide in the middle of the confinement chamber at super-sonic/Alfvénic velocity. During the collision, the merged plasmoid experiences destructive disturbance and loses its fast toroidal flow and characteristic FRC property of having a field-reversed magnetic configuration to become a magnetized plasma without ordered structure. After this dynamic collision, a magnetic configuration of FRC with fast toroidal rotation is self-organized within a few tens of microseconds. This observation indicates robustness of the extremely high-beta, simple magnetic configuration.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.253
Teacher spread0.238 · 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 designObservational
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

Citations27
Published2021
Admission routes1
Has abstractyes

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