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Record W4221165158 · doi:10.1088/1361-6471/ac98f9

The present and future status of heavy neutral leptons

2023· article· en· W4221165158 on OpenAlexaff
Asli M. Abdullahi, Pablo Barham Alzás, Brian Batell, J. B. Beacham, Alexey Boyarsky, Saneli Carbajal, A. Chatterjee, J. I. Crespo-Anadón, Frank F. Deppisch, A. De Roeck, Marco Drewes, A. M. Gago, R. Gonzalez Suarez, E. Goudzovski, A. Hatzikoutelis, Josu Hernández-García, Matheus Hostert, Marco Hufnagel, P. Ilten, A. Izmaylov, Kevin J. Kelly, Juraj Klarić, Joachim Kopp, Suchita Kulkarni, M. Lamoureux, G. Lanfranchi, J. López-Pavón, Oleksii Mikulenko, M. Mooney, Miha Nemevšek, Maksym Ovchynnikov, Silvia Pascoli, Ryan Plestid, M. R. Darwish, F. Redi, Oleg Ruchayskiy, Richard Ruíz, Mikhail Shaposhnikov, L. Shchutska, Ian M. Shoemaker, Robert Shrock, Alex Sousa, N. Van Remortel, Vsevolod Syvolap, Volodymyr Takhistov, Jean‐Loup Tastet, Inar Timiryasov, Aaron C. Vincent, J. S. Yu

Bibliographic record

VenueJournal of Physics G Nuclear and Particle Physics · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicParticle physics theoretical and experimental studies
Canadian institutionsQueen's UniversityPerimeter Institute
FundersHigh Energy PhysicsScience and Technology Facilities CouncilOffice of ScienceNederlandse Organisatie voor Wetenschappelijk OnderzoekU.S. Department of Energy
KeywordsNeutrinoPhysicsLeptonFermionParticle physicsNuclear physics

Abstract

fetched live from OpenAlex

Abstract The existence of nonzero neutrino masses points to the likely existence of multiple Standard Model neutral fermions. When such states are heavy enough that they cannot be produced in oscillations, they are referred to as heavy neutral leptons (HNLs). In this white paper, we discuss the present experimental status of HNLs including colliders, beta decay, accelerators, as well as astrophysical and cosmological impacts. We discuss the importance of continuing to search for HNLs, and its potential impact on our understanding of key fundamental questions, and additionally we outline the future prospects for next-generation future experiments or upcoming accelerator run scenarios.

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)0.004
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0030.004
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.000

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 head0.015
GPT teacher head0.271
Teacher spread0.255 · 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 designTheoretical or conceptual
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

Citations168
Published2023
Admission routes1
Has abstractyes

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