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Record W2171170920 · doi:10.1109/tns.2004.832649

The data acquisition system of the Belle silicon vertex detector (SVD) upgrade

2004· article· en· W2171170920 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

VenueIEEE Transactions on Nuclear Science · 2004
Typearticle
Languageen
FieldPhysics and Astronomy
TopicParticle Detector Development and Performance
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsData acquisitionUpgradeDetectorNuclear electronicsPhysicsSTRIPSConvertersSemiconductor detectorElectrical engineeringElectronic engineeringComputer hardwareComputer scienceEngineeringOpticsVoltageAlgorithm

Abstract

fetched live from OpenAlex

A newly developed data acquisition system (DAQ) for the upgraded silicon vertex detector (SVD2) in the Belle experiment is described. The system consists of 12 PCs connected through PCI I/O boards to 36 flash analog-to-digital converters (FADCs) to read out a system comprising a total of 110 592 strips. It is designed to cope with the increased number of readout channels and the maximum trigger rate of 1 kHz, foreseen in the future operation with higher beam currents. A measurement of the system performance using sparsification algorithm we have developed yields a 1.3-kHz readout rate for a 5% occupancy with less than 5% dead time, which satisfies the requirements on the maximum trigger rate.

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 categoriesScience and technology studies
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 score0.139
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
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.015
GPT teacher head0.233
Teacher spread0.218 · 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