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Use of the ISAC-II Flight Time Monitors toward Automated Tuning

2023· article· en· W6925298529 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJACOW · 2023
Typearticle
Languageen
FieldHealth Professions
TopicNursing Roles and Practices
Canadian institutionsTRIUMF
Fundersnot available
KeywordsCalibrationAutomationEmphasis (telecommunications)PhaserData processingSystem of measurementBeam (structure)Time domain

Abstract

fetched live from OpenAlex

A time-of-flight measurement system has been in use at ISAC-II since 2006 for the phasing of cavities and accurate ion beam velocity measurements across the nuclear chart. This system is heavily relied upon as the primary energy-time domain diagnostic downstream of the ISAC-II linac. Ongoing High Level Applications (HLA) development at TRIUMF has enabled the use of methods that are being applied to these measurements - both for processing and automation of data acquisition. An update will be provided on operational experience with the system over the past 10 years including its recent re-calibration and error analysis. A brief summary of the current HLA framework will be given, including a database for beam measurements and the ability to carry out sequential measurement processes. Finally, the way in which these developments enable beam-based calibration of cavity parameters and a shift to model-based tuning methods is discussed.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.139
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.117
GPT teacher head0.431
Teacher spread0.315 · 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