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Record W7073933787

Reconstruction and identification of pairs of collimated $\\tau$-leptons decaying hadronically using $\\sqrt{s}=13$ TeV $pp$ collision data with the ATLAS detector

2024· other· en· W7073933787 on OpenAlexfundno aff

Bibliographic record

VenueCERN Document Server (European Organization for Nuclear Research) · 2024
Typeother
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Imaging and Inversion Techniques
Canadian institutionsnot available
FundersH2020 Marie Skłodowska-Curie ActionsH2020 European Research CouncilInstitut National de Physique Nucléaire et de Physique des ParticulesAgencia Estatal de InvestigaciónFundação para a Ciência e a TecnologiaMinistry of Education, Culture, Sports, Science and TechnologyBundesministerium für Bildung und ForschungNatural Sciences and Engineering Research Council of CanadaAgencia Nacional de Promoción Científica y TecnológicaSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungScience and Technology Facilities CouncilHorizon 2020 Framework ProgrammeNarodowa Agencja Wymiany AkademickiejForskningsrådet om Hälsa, Arbetsliv och VälfärdMinisterstvo Školství, Mládeže a TělovýchovyNational Science and Technology CouncilEuropean Social FundRoyal SocietyCentre National pour la Recherche Scientifique et TechniqueBritish Columbia Knowledge Development FundMax-Planck-GesellschaftEuropean Regional Development FundCentre National de la Recherche ScientifiqueU.S. Department of EnergyFundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de JaneiroIsrael Science FoundationJapan Society for the Promotion of ScienceMinisterstwo Edukacji i NaukiConselho Nacional de Desenvolvimento Científico e TecnológicoBundesministerium für Wissenschaft, Forschung und WirtschaftGeneralitat de CatalunyaGeneralitat ValencianaAgencia Nacional de Investigación y DesarrolloGrantová Agentura České RepublikyAustrian Science FundNational Natural Science Foundation of ChinaEuropean CommissionLeverhulme TrustFundação de Amparo à Pesquisa do Estado de São PauloDeutsche ForschungsgemeinschaftNederlandse Organisatie voor Wetenschappelijk OnderzoekMinistry of Science and Technology of the People's Republic of ChinaAgence Nationale de la RechercheUK Research and InnovationNational Science FoundationAlexander von Humboldt-StiftungTRIUMFDanmarks GrundforskningsfondTürkiye Enerji, Nükleer ve Maden Araştırma KurumuCanarieCentres de Recerca de CatalunyaCERN
KeywordsCollisionLarge Hadron ColliderAtlas (anatomy)LuminosityDetectorCollimated lightIdentification (biology)Reconstruction algorithmHadron
DOInot available

Abstract

fetched live from OpenAlex

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 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)0.001
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.033
GPT teacher head0.263
Teacher spread0.229 · 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
Published2024
Admission routes1
Has abstractyes

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