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Search for heavy neutral leptons in <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si1.svg"> <mml:msup> <mml:mi>π</mml:mi> <mml:mo>+</mml:mo> </mml:msup> </mml:math> decays to positrons

2025· preprint· en· W4414575964 on OpenAlexfundno aff
B. Bloch-Devaux, E. Cortina, Z. Hives, N. Canale, Ottorino Frezza

Bibliographic record

VenuePhysics Letters B · 2025
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicParticle physics theoretical and experimental studies
Canadian institutionsnot available
FundersHorizon 2020 Framework ProgrammeScience and Technology Facilities CouncilMinistero dell’Istruzione, dell’Università e della RicercaMinisterstvo školstva, vedy, výskumu a športu Slovenskej republikyEuropean Research CouncilInstitutul de Fizică AtomicăGrantová Agentura České RepublikyFonds De La Recherche Scientifique - FNRSBundesministerium für Bildung und ForschungMinisterstvo Školství, Mládeže a TělovýchovyAgence Nationale de la RechercheConsejo Nacional de Ciencia y TecnologíaRoyal SocietyNational Science FoundationNatural Sciences and Engineering Research Council of CanadaMinistère de l’Enseignement Supérieur et de la Recherche ScientifiqueIstituto Nazionale di Fisica NucleareCERNUniverzita Karlova v Praze
KeywordsLeptonNeutrinoLarge Hadron ColliderPositronMixing (physics)Range (aeronautics)Standard Model (mathematical formulation)Lepton numberPontecorvo–Maki–Nakagawa–Sakata matrix

Abstract

fetched live from OpenAlex

A search for heavy neutral lepton ($N$) production in $π^+\to e^+ N$ in-flight decays using data collected by the NA62 experiment at CERN in 2017-2024 is reported. Upper limits for the extended neutrino mixing matrix element $|U_{e4}|^2$ are established at the level of $10^{-8}$ for heavy neutral leptons with mass in the range 95-126 $MeV/c^2$ and lifetime exceeding 50 ns.

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)0.001
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.021
GPT teacher head0.271
Teacher spread0.250 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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