MétaCan
Menu
Back to cohort
Record W4313267545 · doi:10.1364/oe.480624

Upgraded Cherenkov time-of-flight detector for the AFP project

2022· article· en· W4313267545 on OpenAlexaff
L. Nožka, G. Avoni, E. Banaś, A. Brandt, Paul M. Davis, Serge Duarte Pinto, Vjačeslav Georgiev, M. Hrabovský, T. Komárek, K. Korcyl, I. López Paz, M. Milovanović, Goran Mladenović, D. A. Orlov, M. Rijssenbeek, Petr Schovánek, T. Sýkora, M. Trzebiński, V. Urbášek, Jan Zich

Bibliographic record

VenueOptics Express · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicRadiation Detection and Scintillator Technologies
Canadian institutionsUniversity of Alberta
FundersEuropean Regional Development FundCERNMinisterstwo Edukacji i NaukiUniverzita Palackého v OlomouciNarodowe Centrum NaukiMinistarstvo Prosvete, Nauke i Tehnološkog RazvojaMinisterstvo Školství, Mládeže a Tělovýchovy
KeywordsCherenkov radiationLarge Hadron ColliderPhotomultiplierDetectorPhysicsOpticsCherenkov detectorRadiation hardeningSilicon photomultiplierRadiationNuclear physicsScintillator

Abstract

fetched live from OpenAlex

We present the results of our performance studies of the upgraded Cherenkov time-of-flight (ToF) detector for the AFP (ATLAS Forward Proton) project. The latest version consists of solid L-shaped fused silica bars, new customized ALD-coated micro-channel plate photomultipliers (MCP-PMTs) miniPlanacon XPM85112-S-R2D2 with an extended lifetime which operate at low gains (order of 10 3 ), and an updated construction. The improvements were aimed to increase the efficiency, the lifetime as well as the radiation hardness of the detector which has been designed to operate in high radiation areas (above 400 kGy/year). The detector was finally tested at the CERN-SPS test-beam facility (120 GeV π + particles) in August 2021 prior to its installation at the Large Hadron Collider (LHC) at CERN. Measurements proved the detector kept its inner timing resolution of 20 ps despite the rather low gain of its photodetector and reduced optical throughput caused by inevitable changes in the detector geometry.

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 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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.383
Threshold uncertainty score0.475

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 communication0.0000.000
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 head0.021
GPT teacher head0.256
Teacher spread0.236 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations4
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueOptics ExpressSame topicRadiation Detection and Scintillator TechnologiesFrench-language works237,207