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Record W4221156006 · doi:10.1088/1361-6633/ac9cee

New physics searches at kaon and hyperon factories

2022· article· en· W4221156006 on OpenAlexaff
Goudzovski, Evgueni, Diego Redigolo, Kohsaku Tobioka, Jure Zupan, Gonzalo Alonso-Álvarez, Daniele S. M. Alves, Saurabh Bansal, Martin Bauer, Joachim Brod, V. Chobanova, Giancarlo D’Ambrosio, Alakabha Datta, Avital Dery, F. Dettori, Bogdan A. Dobrescu, Babette Döbrich, Daniel Egaña-Ugrinovic, Gilly Elor, M. Fabbrichesi, B. Fornal, Patrick J. Fox, Emidio Gabrielli, Li‐Sheng Geng, V. V. Gligorov, Martin Gorbahn, Benjamı́n Grinstein, Diego Guadagnoli, Samuel Homiller, Matheus Hostert, Kevin J. Kelly, Teppei Kitahara, Simon Knapen, Gordan Krnjaic, Sandra Kvedaraitė, G. Lanfranchi, Danny Marfatia, Jorge Martin Camalich, D. Martínez Santos, K. Massri, Patrick Meade, M. Moulson, H. Nanjo, Matthias Neubert, Maxim Pospelov, Sophie Renner, Stefan Schacht, Marvin Schnubel, Rui-Xiang Shi, Brian Shuve, T. Spadaro, Yotam Soreq, Emmanuel Stamou, Olcyr Sumensari, Michele Tammaro, Jorge Terol-Calvo, Andrea Thamm, Yu-Chen Tung, Kei Yamamoto, Robert Ziegler

Bibliographic record

VenueReports on Progress in Physics · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicParticle physics theoretical and experimental studies
Canadian institutionsPerimeter InstituteMcGill University
FundersHigh Energy PhysicsDivision of PhysicsNational Key Research and Development Program of ChinaScience and Technology Facilities CouncilJapan Society for the Promotion of ScienceHorizon 2020 Framework ProgrammeOffice of ScienceJavna Agencija za Raziskovalno Dejavnost RSChina Postdoctoral Science FoundationChinese Academy of SciencesH2020 Marie Skłodowska-Curie ActionsMinisterio de Economía y CompetitividadNational Natural Science Foundation of ChinaU.S. Department of EnergyEuropean CommissionLos Alamos National LaboratoryAlexander von Humboldt-StiftungEngineering and Physical Sciences Research CouncilUK Research and InnovationAlfred P. Sloan FoundationMinisterio de Ciencia e InnovaciónResearch Corporation for Science AdvancementNational Science Foundation
KeywordsHyperonPhysicsParticle physicsNuclear physicsHadron

Abstract

fetched live from OpenAlex

Rare meson decays are among the most sensitive probes of both heavy and light new physics. Among them, new physics searches using kaons benefit from their small total decay widths and the availability of very large datasets. On the other hand, useful complementary information is provided by hyperon decay measurements. We summarize the relevant phenomenological models and the status of the searches in a comprehensive list of kaon and hyperon decay channels. We identify new search strategies for under-explored signatures, and demonstrate that the improved sensitivities from current and next-generation experiments could lead to a qualitative leap in the exploration of light dark sectors.

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.

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)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.005
Science and technology studies0.0010.001
Scholarly communication0.0020.004
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.002

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 head0.025
GPT teacher head0.292
Teacher spread0.267 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations1
Published2022
Admission routes1
Has abstractyes

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