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Прототип протонного ондуляторного линейного ускорителя

2021· article· en· W3167929588 on OpenAlexaff
Sergey Kutsaev, Н.В. Аврелин, А.Н. Аврелин, R. Agustsson, Jonathan Edelen, A. Mypox, А.Ю. Смирнов

Bibliographic record

VenueПисьма в журнал технической физики · 2021
Typearticle
Languageen
FieldEngineering
TopicParticle Accelerators and Free-Electron Lasers
Canadian institutionsUniversity of British ColumbiaTRIUMF
Fundersnot available
KeywordsUndulatorPhysicsTransverse planeResonatorLinear particle acceleratorAccelerationParticle acceleratorProtonField (mathematics)MagnetOpticsBeam (structure)Computational physicsNuclear physicsClassical mechanicsQuantum mechanicsEngineering

Abstract

fetched live from OpenAlex

One of the ways to realize undulator acceleration is to ensure particles motion in a magnetostatic undulator, where spatial oscillations of particles in the transverse direction are synchronized with temporal oscillations of transverse high-frequency field, which allows its energy transfer to the accelerated particles. The resonators, tcapable to provide a uniform transverse field, are structurally simpler than resonators with a periodically variable longitudinal field, which makes undulator accelerators an attractive alternative to coventional accelerators.Although the physics of such accelerators was previously descussed in the literature, the task of creating a physical prototype of undulator linac is still not realized. In this paper, we privde a practical description of the project of a proton undulator linear accelerator based on based on this principle, developed by RadiaBeam (USA).

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.018
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0180.007

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 head0.005
GPT teacher head0.171
Teacher spread0.166 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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