MétaCan
Menu
Back to cohort
Record W3042673143 · doi:10.1016/j.nima.2020.164562

CsI(Tl) pulse shape discrimination with the Belle II electromagnetic calorimeter as a novel method to improve particle identification at electron–positron colliders

2020· article· en· W3042673143 on OpenAlexafffund
S. Longo, J. M. Roney, C. Cecchi, S. Cunliffe, T. Ferber, H. Hayashii, C. Hearty, A. D. Hershenhorn, A. Kuzmin, E. Manoni, F. Meier, K. Miyabayashi, I. Nakamura, M. Remnev, A. Sibidanov, Y. Unno, Y. Usov, V. Zhulanov

Bibliographic record

VenueNuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicRadiation Detection and Scintillator Technologies
Canadian institutionsUniversity of British ColumbiaInstitute of Particle PhysicsUniversity of Victoria
FundersInstitut National de Physique Nucléaire et de Physique des ParticulesAkademi Sains MalaysiaJapan Society for the Promotion of ScienceNatural Sciences and Engineering Research Council of CanadaCentro de Investigación y de Estudios Avanzados del Instituto Politécnico NacionalIstituto Nazionale di Fisica NucleareNational Institute of InformaticsMinistry of Science and Higher Education of the Russian FederationBundesministerium für Bildung, Wissenschaft und ForschungMinistry of Education and Science of UkraineTürkiye Bilimsel ve Teknolojik Araştırma KurumuNational Foundation for Science and Technology DevelopmentMax-Planck-GesellschaftMinistry of Education, Culture, Sports, Science and TechnologyKorea Institute of Science and Technology InformationLiaoning Revitalization Talents ProgramBundesministerium für Bildung und ForschungMinisterstvo Školství, Mládeže a TělovýchovyKorea Institute of Science and TechnologyThailand Center of Excellence in PhysicsUnited States-Israel Binational Science FoundationGeneralitat ValencianaNational Research FoundationAustrian Science FundCAS Center for Excellence in Particle PhysicsChinese Academy of SciencesU.S. Department of EnergyNational Natural Science Foundation of ChinaAlexander von Humboldt-StiftungCompute CanadaUniversity of TabukNational Science FoundationCanarieDeutsche ForschungsgemeinschaftJavna Agencija za Raziskovalno Dejavnost RSCentre National de la Recherche ScientifiqueUniverzita Karlova v Praze
KeywordsPhysicsScintillationParticle identificationCalorimeter (particle physics)PhotonPositronHadronNuclear physicsElectronPulse (music)OpticsLarge Hadron ColliderDetector

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.035
GPT teacher head0.351
Teacher spread0.316 · 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
GenreMethods

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

Citations22
Published2020
Admission routes2
Has abstractno

Explore more

Same venueNuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated EquipmentSame topicRadiation Detection and Scintillator TechnologiesFrench-language works237,207