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EUDAQ—a data acquisition software framework for common beam telescopes

2020· article· en· W2975802096 on OpenAlex
P. Ahlburg, S. Arfaoui, J.-H. Arling, Heiko Augustin, David Barney, M. Benoit, T. Bisanz, E. Corrin, D. Cussans, D. Dannheim, Jan Dreyling-Eschweiler, T. Eichhorn, A. Fiergolski, I. M. Gregor, J. Große-Knetter, D. Haas, Lennart Huth, A. Irles Quiles, H. Jansen, J. Janssen, M. Keil, J. S. Keller, M. Kiehn, H. J. Kim, J. Kroll, K. Krüger, S. Kulis, J. Kvasnička, J. S. Lange, Yi Liu, F. Lütticke, C. Mariñas, P. Martinengo, A. Nürnberg, B. Paschen, H. Perrey, R. Peschke, D. Pitzl, D. Pohl, A. Quadt, T. Quast, F. Reidt, E. Rossi, I. Rubinsky, A. Rummler, H. Schreeck, P. Schütze, B. Schwenker, Simon Spannagel, M. M. Stanitzki, U. Stolzenberg, Taikan Suehara, M. Šuljić, G. Troska, Mónika Varga-Kőfaragó, J. Weingarten, P. Wieduwilt

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

VenueJournal of Instrumentation · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicParticle Detector Development and Performance
Canadian institutionsCarleton University
Fundersnot available
KeywordsData acquisitionSoftwareReliability (semiconductor)Beam (structure)Computer scienceDetectorTelescopeRange (aeronautics)Resource (disambiguation)Computer hardwareSystems engineeringPhysicsAerospace engineeringOpticsOperating systemTelecommunicationsEngineering

Abstract

fetched live from OpenAlex

EUDAQ is a generic data acquisition software developed for use in conjunction with common beam telescopes at charged particle beam lines. Providing high-precision reference tracks for performance studies of new sensors, beam telescopes are essential for the research and development towards future detectors for high-energy physics. As beam time is a highly limited resource, EUDAQ has been designed with reliability and ease-of-use in mind. It enables flexible integration of different independent devices under test via their specific data acquisition systems into a top-level framework. EUDAQ controls all components globally, handles the data flow centrally and synchronises and records the data streams. Over the past decade, EUDAQ has been deployed as part of a wide range of successful test beam campaigns and detector development applications.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.676
Threshold uncertainty score0.254

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 studies0.0000.000
Scholarly communication0.0000.001
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 head0.045
GPT teacher head0.313
Teacher spread0.268 · 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