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Measurement of double-differential charged-current Drell-Yan cross-sections at high transverse masses in <i>pp</i> collisions at √<i>s</i>=13 TeV with the ATLAS detector
Bibliographic record
VenueApollo (University of Cambridge) · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicCrystallography and Radiation Phenomena
Canadian institutionsnot available
FundersH2020 European Research CouncilEuropean Social FundHigh Energy PhysicsSLAC National Accelerator LaboratoryAgencia Estatal de InvestigaciónAgencia Nacional de Promoción Científica y TecnológicaUniversity of Illinois at Urbana-ChampaignStony Brook UniversityAgencia Nacional de Investigación y DesarrolloShanghai Key Laboratory for Particle Physics and CosmologyPontificia Universidad Católica de ChileUniversidade do MinhoUniversity of West AtticaJulius-Maximilians-Universität WürzburgUniversidad de TarapacáConselho Nacional de Desenvolvimento Científico e TecnológicoUniversité Paris-SaclayUniverzita Palackého v OlomouciNorthern Illinois UniversityForskningsrådet om Hälsa, Arbetsliv och VälfärdUniversity of TsukubaAristotle University of ThessalonikiTokyo Metropolitan UniversityTechnion-Israel Institute of TechnologyNarodowa Agencja Wymiany AkademickiejUnited Arab Emirates UniversityJapan Society for the Promotion of ScienceUniversidade de CoimbraUniversitetet i OsloCERNMinistry of Education, IndiaShanghai Jiao Tong UniversitySimon Fraser UniversityUniversidad de GranadaSorbonne UniversitéKungliga Tekniska HögskolanAkademie Věd České RepublikyEuropean Regional Development FundBritish Columbia Knowledge Development FundCentre National de la Recherche ScientifiqueMax-Planck-GesellschaftBundesministerium für Wissenschaft, Forschung und WirtschaftUniversity of TorontoGeneralitat ValencianaH2020 Marie Skłodowska-Curie ActionsUniverzita Karlova v PrazeGeneralitat de CatalunyaAcademia SinicaUniversiteit van AmsterdamAustrian Science FundUniversity of PennsylvaniaGrantová Agentura České RepublikyNatural Sciences and Engineering Research Council of CanadaUniversity of OregonMinistry of Education, Culture, Sports, Science and TechnologyInstituto Superior TécnicoBundesministerium für Bildung und ForschungNational Science and Technology CouncilMinisterstvo Školství, Mládeže a TělovýchovyLeverhulme TrustEuropean CommissionFundação de Amparo à Pesquisa do Estado de São PauloDanmarks GrundforskningsfondDeutsche ForschungsgemeinschaftNederlandse Organisatie voor Wetenschappelijk OnderzoekInstitut National de Physique Nucléaire et de Physique des ParticulesUniversidade de LisboaMinistry of Science and Technology of the People's Republic of ChinaAgence Nationale de la RechercheUniversity of SussexCentre National pour la Recherche Scientifique et TechniqueRoyal SocietyScience and Technology Facilities CouncilSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungYork UniversityHorizon 2020 Framework ProgrammeOklahoma State UniversityNational Science FoundationNew York University Abu DhabiUK Research and InnovationCentres de Recerca de CatalunyaZhengzhou UniversityUniversity of California, IrvineCHIST-ERAFundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de JaneiroU.S. Department of EnergyShandong UniversityUniversidad Técnica Federico Santa MaríaUniversität SiegenCanarieTel Aviv UniversityUniversity of PittsburghUniversity of OxfordAlexander von Humboldt-StiftungTRIUMFUniversity of OklahomaRadboud UniversiteitFundação para a Ciência e a TecnologiaUniversity of WashingtonMinisterstwo Edukacji i NaukiDivision of PhysicsTürkiye Enerji, Nükleer ve Maden Araştırma KurumuNational Natural Science Foundation of ChinaOhio State UniversityČeské Vysoké Učení Technické v Praze
KeywordsElectroweak interactionMuonLeptonPartonLarge Hadron ColliderTransverse planeDrell–Yan processDetectorQuantum chromodynamicsAtlas (anatomy)
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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 head0.009
GPT teacher head0.208
Teacher spread0.199 · 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 designObservational
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
Published2025
Admission routes1
Has abstractyes