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Record W7071478196

Search for heavy neutrinos with the T2K near detector ND280

2019· article· en· W7071478196 on OpenAlexfundno aff

Bibliographic record

VenueLancaster EPrints (Lancaster University) · 2019
Typearticle
Languageen
FieldComputer Science
TopicQR Code Applications and Technologies
Canadian institutionsnot available
FundersInstitut National de Physique Nucléaire et de Physique des ParticulesDeutsches Elektronen-SynchrotronScience and Technology Facilities CouncilJapan Society for the Promotion of ScienceHorizon 2020 Framework ProgrammeRussian Foundation for Basic ResearchRussian Science FoundationMinistry of Education, Culture, Sports, Science and TechnologyEuropean Regional Development FundU.S. Department of EnergyEuropean CommissionCentre National de la Recherche ScientifiqueWestern Canada Research GridDeutsche ForschungsgemeinschaftCERNCompute CanadaNatural Sciences and Engineering Research Council of CanadaAlfred P. Sloan FoundationSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
KeywordsNeutrinoDetectorNeutrino oscillationMassless particleRange (aeronautics)Mixing (physics)Neutrino detectorBeam (structure)
DOInot available

Abstract

fetched live from OpenAlex

This paper reports on the search for heavy neutrinos with masses in the range 140<MN<493 MeV/c2 using the off-axis near detector ND280 of the T2K experiment. These particles can be produced from kaon decays in the standard neutrino beam and then subsequently decay in ND280. The decay modes under consideration are N→ℓα±π and N→ℓα+ℓβ-ν(-)(α,β=e,μ). A search for such events has been made using the Time Projection Chambers of ND280, where the background has been reduced to less than two events in the current dataset in all channels. No excess has been observed in the signal region. A combined Bayesian statistical approach has been applied to extract upper limits on the mixing elements of heavy neutrinos to electron-, muon- and tau- flavored currents (Ue2, Uμ2, Uτ2) as a function of the heavy neutrino mass, e.g., Ue2<10-9 at 90% C.L. for a mass of 390 MeV/c2. These constraints are competitive with previous experiments.

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 score0.006
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.002

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 head0.017
GPT teacher head0.205
Teacher spread0.188 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

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