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Record W2147800966 · doi:10.1109/pac.2003.1288570

A mechanical tuner for the ISAC-II quarter wave superconducting cavities

2004· article· en· W2147800966 on OpenAlexaff
T. Ries, K. Fong, Shane Koscielniak, Robert Laxdal, G. Stanford

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicParticle accelerators and beam dynamics
Canadian institutionsTRIUMF
Fundersnot available
KeywordsTunerPhysicsBandwidth (computing)Linear particle acceleratorMaterials sciencePhase-locked loopElectrical engineeringAcousticsOpticsRadio frequencyBeam (structure)EngineeringPhase noiseTelecommunications

Abstract

fetched live from OpenAlex

TRIUMF is developing a new mechanical tuner system capable of both coarse (kHz) and fine (Hz) frequency adjustments for maintaining frequency lock on the superconducting quarter wave cavities of the ISAC-II heavy ion linac. A 1 mm thick Niobium plate at the high field end of the cavity is actuated by a vertically mounted permanent magnet linear servo motor, at the top of the cryostat, using a 'zero backlash' lever and push rod configuration through a bellows feed-through. The system resolution at the tuner plate center is /spl sim/0.055 /spl mu/m (0.3 Hz) with a dynamic range of 8 KHz and a manual coarse tuning range of 33 kHz. In cold tests with a prototype quarter wave cavity the tuning system's ability to compensate perturbations indicated a bandwidth up to 100 Hz. A large mechanical resonance at 20 Hz should be eliminated in the on-line device. The rf control is based on a self-excited loop with a locking circuit for amplitude and phase regulation. The tuner is fed a position signal integrated from the control loop phase error. Details of the mechanical device and results of open and closed loop cold tests will be given.

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)0.001
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 score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.029
GPT teacher head0.230
Teacher spread0.201 · 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

Citations29
Published2004
Admission routes1
Has abstractyes

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