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Performance of the ATLAS forward proton Time-of-Flight detector in Run 2
Nuno Filipe Castro, A. Onofre, ATLAS Collaboration
Bibliographic record
VenueRepositóriUM (Universidade do Minho) · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicParticle Detector Development and Performance
Canadian institutionsnot available
FundersCHIST-ERAH2020 Marie Skłodowska-Curie ActionsFundação para a Ciência e a TecnologiaJapan Society for the Promotion of ScienceNarodowa Agencja Wymiany AkademickiejIstituto Nazionale di Fisica NucleareState Key Laboratory of Particle Detection and ElectronicsAgencia Nacional de Investigación y DesarrolloStockholms UniversitetUniversität InnsbruckUniversity of Science and Technology of ChinaUniversidade Federal do Rio de JaneiroUniversidade Federal de Juiz de ForaUniversité Paris-SaclayUniversidade do Estado do Rio de JaneiroHigh Energy Accelerator Research OrganizationInstitut National de Physique Nucléaire et de Physique des ParticulesUniversité de GenèveUniversité de FribourgUniversidade de São PauloDeutsches Elektronen-SynchrotronBanco Bilbao Vizcaya ArgentariaNational Tsing Hua UniversityShanghai Jiao Tong UniversityMinisterio de Ciencia e InnovaciónUniversità degli Studi di PaviaMinistry of Education, IndiaHorizon 2020 Framework ProgrammeVetenskapsrådetJavna Agencija za Raziskovalno Dejavnost RSAgence Nationale de la RechercheSapienza Università di RomaIsrael Science FoundationConselho Nacional de Desenvolvimento Científico e TecnológicoBundesministerium für Wissenschaft, Forschung und WirtschaftGeneralitat de CatalunyaGeneralitat ValencianaTechnische Universität DresdenAustrian Science FundEuropean CommissionLeverhulme TrustFundação de Amparo à Pesquisa do Estado de São PauloUniversità di PisaDanmarks GrundforskningsfondShanghai Key Laboratory for Particle Physics and CosmologyKnut och Alice Wallenbergs StiftelseUniversität HeidelbergScience and Technology Facilities CouncilSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungUniversity of GlasgowNatural Sciences and Engineering Research Council of CanadaMinistry of Education, Culture, Sports, Science and TechnologyBundesministerium für Bildung und ForschungUniversité Grenoble AlpesMinisterstvo Školství, Mládeže a TělovýchovyIowa State UniversityNational Natural Science Foundation of ChinaScottish Universities Physics AllianceSouthern Methodist UniversityAlbert-Ludwigs-Universität FreiburgAgencia Nacional de Promoción Científica y TecnológicaGeorg-August-Universität GöttingenNederlandse Organisatie voor Wetenschappelijk OnderzoekDeutsche ForschungsgemeinschaftCentres de Recerca de CatalunyaZhengzhou UniversityCERNU.S. Department of EnergyShandong UniversityJustus Liebig Universität GießenEuropean Regional Development FundBritish Columbia Knowledge Development FundCentre National de la Recherche ScientifiqueMax-Planck-GesellschaftEuropean Social FundCentre National pour la Recherche Scientifique et TechniqueRoyal SocietyAlexander von Humboldt-StiftungTRIUMFNational Science FoundationUniversità degli Studi di TrentoBaden-Württemberg StiftungUniversità degli Studi di Napoli Federico IINorges ForskningsrådFundación BBVATechnische Universität DortmundAbdus Salam International Centre for Theoretical PhysicsTürkiye Enerji, Nükleer ve Maden Araştırma KurumuUniversità della CalabriaCanarieHarvard University
KeywordsAtlas (anatomy)DetectorAtlas detectorLarge Hadron ColliderPosition (finance)Interaction point
DOInot available
Abstract
OpenAlex records an abstract for this work, but it could not be fetched just now.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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)0.001
metaresearch head score (Gemma)0.002
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 score0.010
Threshold uncertainty score0.019
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 head0.005
GPT teacher head0.201
Teacher spread0.196 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine 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".
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Citations0
Published2024
Admission routes1
Has abstractyes