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Controls Interface into the Low-Level RF System in the ARIEL e-Linac at TRIUMF

2015· article· en· W2558868213 on OpenAlexaff
J.J. Pon, Keiko Ezawa, R. Keitel, R. Nussbaumer, Jane Richards, Mike Rowe, P.J. Yogendran

Bibliographic record

VenueJACOW · 2015
Typearticle
Languageen
FieldEngineering
TopicParticle accelerators and beam dynamics
Canadian institutionsTRIUMF
Fundersnot available
KeywordsLinear particle acceleratorInterface (matter)PhysicsComputer scienceBeam (structure)OpticsOperating system

Abstract

fetched live from OpenAlex

Phase 1 of TRIUMF Advanced Rare Isotope Laboratory (ARIEL) was completed in September 2014. At phase 1, the Low-Level RF (LLRF) system of ARIEL's electron linear accelerator (e-Linac) consists of a buncher and a deflector, one single-cavity injector cryomodule and the first cavity of two dual-cavity accelerating cryomodules. The model for the e-Linac LLRF system is largely based on the experience gained from the fully-commissioned TRIUMF ISAC-II linear accelerator (linac). Similarly, the EPICS-based Controls for the e-Linac LLRF builds on the lessons learned with the linac LLRF Controls. This paper describes the interface between the ARIEL Control System (ACS) and the e-Linac LLRF using EPICS ASYN/StreamDevice and a SCPI-like protocol. Also discussed are the ACS EDM displays and future plans for LLRF Controls.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.511
Threshold uncertainty score0.290

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.027
GPT teacher head0.243
Teacher spread0.216 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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
Published2015
Admission routes1
Has abstractyes

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