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.
fundA Canadian funder is recorded on the work.
VenueThe European Physical Journal C · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicParticle physics theoretical and experimental studies
Canadian institutionsYork UniversityUniversity of British ColumbiaTRIUMFCarleton UniversitySimon Fraser UniversityUniversity of AlbertaUniversité de MontréalInstitute of Particle PhysicsMcGill UniversityUniversity of VictoriaUniversity of Toronto
FundersH2020 Marie Skłodowska-Curie ActionsInstitut National de Physique Nucléaire et de Physique des ParticulesAgencia Nacional de Promoción Científica y TecnológicaFundação para a Ciência e a TecnologiaSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungScience and Technology Facilities CouncilBundesministerium für Bildung und ForschungMinistry of Education, Culture, Sports, Science and TechnologyNatural Sciences and Engineering Research Council of CanadaFondation Partager le SavoirEuropean Social FundRoyal SocietyCentre National pour la Recherche Scientifique et TechniqueShota Rustaveli National Science FoundationJapan Society for the Promotion of ScienceNational Research Center "Kurchatov Institute"European Regional Development FundBritish Columbia Knowledge Development FundMax-Planck-GesellschaftCentre National de la Recherche ScientifiqueIsrael Science FoundationComisión Nacional de Investigación Científica y TecnológicaTürkiye Atom Enerjisi KurumuJoint Institute for Nuclear ResearchMinisterstwo Edukacji i NaukiConselho Nacional de Desenvolvimento Científico e TecnológicoBundesministerium für Wissenschaft, Forschung und WirtschaftGeneralitat de CatalunyaGeneralitat ValencianaFonds Québécois de la Recherche sur la Nature et les TechnologiesAustrian Science FundIsraeli Centers for Research ExcellenceU.S. Department of EnergyOntario Innovation TrustNational Natural Science Foundation of ChinaEuropean CommissionLeverhulme TrustFundação de Amparo à Pesquisa do Estado de São PauloJavna Agencija za Raziskovalno Dejavnost RSDeutsche ForschungsgemeinschaftNederlandse Organisatie voor Wetenschappelijk OnderzoekAgence Nationale de la RechercheServices Fédéraux des Affaires Scientifiques, Techniques et CulturellesDepartment of Science and Technology, Ministry of Science and Technology, IndiaGeneral Secretariat for Research and TechnologyNational Science FoundationCompute CanadaAlexander von Humboldt-StiftungTRIUMFDepartamento Administrativo de Ciencia, Tecnología e Innovación (COLCIENCIAS)Centres de Recerca de CatalunyaCERNDanmarks GrundforskningsfondCanarie
KeywordsCalorimeter (particle physics)PhysicsLarge Hadron ColliderNuclear physicsAtlas (anatomy)DetectorHadronJet (fluid)Charged particleAtlas detectorATLAS experimentParticle (ecology)Particle physicsOpticsMechanicsIon
Abstract
fetched live from OpenAlexThis paper describes the implementation and performance of a particle flow algorithm applied to 20.2 fb[Formula: see text] of ATLAS data from 8 TeV proton-proton collisions in Run 1 of the LHC. The algorithm removes calorimeter energy deposits due to charged hadrons from consideration during jet reconstruction, instead using measurements of their momenta from the inner tracker. This improves the accuracy of the charged-hadron measurement, while retaining the calorimeter measurements of neutral-particle energies. The paper places emphasis on how this is achieved, while minimising double-counting of charged-hadron signals between the inner tracker and calorimeter. The performance of particle flow jets, formed from the ensemble of signals from the calorimeter and the inner tracker, is compared to that of jets reconstructed from calorimeter energy deposits alone, demonstrating improvements in resolution and pile-up stability.
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 imitationNot 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 categoriesScience and technology studies
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 score0.754
Threshold uncertainty score0.999
Codex and Gemma teacher scores by category
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.
Teacher spread0.230 · 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
