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Record W2138270895 · doi:10.1109/ccece.2005.1557438

Performance measurements of the lucid data acquisition system

2006· article· en· W2138270895 on OpenAlexaffabout
Daron Chabot, R. Igarashi, D.E. Dodds, W.E. Norum

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNuclear Physics and Applications
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsData acquisitionDead timeDigitizationScope (computer science)Computer scienceEvent (particle physics)DetectorOperating systemPhysicsTelecommunications

Abstract

fetched live from OpenAlex

The Lucid data acquisition and analysis system, developed by the experimental subatomic physics group at the University of Saskatchewan, has undergone several recent upgrades. Currently, Lucid is used in conjunction with the blowfish neutron detector at the high intensity gamma source facility at Duke University, North Carolina. Changes to the acquisition system were partially motivated by upgrades to blowfish and to the Duke facility itself, which will result in an increase of available gamma ray flux. This increased flux translates directly to an increase in the event rate as seen by the acquisition system. The scope of the system upgrades include changes to the type of digitization modules, acquisition control computer, and real time operating system. The new system's dead time and the underlying processes comprising the dead time were measured and are presented here

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)0.004
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 score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.003

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 head0.232
Teacher spread0.205 · 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

Citations0
Published2006
Admission routes2
Has abstractyes

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