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First RF Test Results of Two-Cavities Accelerating Cryomodule for ARIEL eLinac at TRIUMF

2018· article· en· W3082865541 on OpenAlexaff
Yanyun Ma, Z. Ang, K. Fong, James Keir, David Kishi, Devon Lang, Robert Laxdal, Ruslan Nagimov, Bhalwinder Waraich, Zhongyuan Yao, Vladimir Zvyagintsev

Bibliographic record

VenueJACOW · 2018
Typearticle
Languageen
FieldEngineering
TopicParticle accelerators and beam dynamics
Canadian institutionsTRIUMF
Fundersnot available
KeywordsPhysicsTest (biology)Nuclear physicsGeology

Abstract

fetched live from OpenAlex

The Advanced Rare Isotope Laboratory (ARIEL) pro-ject requires a 50 MeV, 10 mA continuous-wave (CW) electron linear accelerator (e-Linac) as a driver accelera-tor. Now the stage of the 30MeV portion of the e-Linac is under commissioning which includes an injector cry-omodule(ICM) and the 1st accelerator cryomodules (ACM1) with two cavities configuration. A single 290kW klystron is used to feed the two ACM1 cavities in vector sum closed-loop control. In this paper the initial commis-sioning results of the ACM1 RF system will be present.

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)0.002
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.025
GPT teacher head0.255
Teacher spread0.230 · 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

Citations3
Published2018
Admission routes1
Has abstractyes

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