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Record W6996319902

A search for $hep$ solar neutrinos and the diffuse supernova neutrino background using all three phases of the Sudbury Neutrino Observatory

2020· article· en· W6996319902 on OpenAlexfundaboutno aff

Bibliographic record

VenueLancaster EPrints (Lancaster University) · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNeutrino Physics Research
Canadian institutionsnot available
FundersScience and Technology Facilities CouncilNational Nuclear Security AdministrationQueen's UniversityIndustry CanadaCanada Research ChairsAlfred P. Sloan FoundationNuclear PhysicsStrongFundação para a Ciência e a TecnologiaU.S. Department of EnergyNational Science Foundation
KeywordsSolar neutrinoSupernovaNeutrinoObservatoryFlux (metallurgy)Neutrino detectorSolar neutrino problemComponent (thermodynamics)
DOInot available

Abstract

fetched live from OpenAlex

A search has been performed for neutrinos from two sources, the $hep$ reaction in the solar $pp$ fusion chain and the $\nu_e$ component of the diffuse supernova neutrino background (DSNB), using the full dataset of the Sudbury Neutrino Observatory. The $hep$ search is performed using both a single-bin counting analysis and a likelihood fit. We find a best-fit flux that is compatible with solar model predictions while remaining consistent with zero flux, and set a one-sided upper limit of $\Phi_{hep} <30\times10^{3}~\mathrm{cm}^{-2}~\mathrm{s}^{-1}$ (90% credible interval). No events are observed in the DSNB search region, and we also set an improved upper bound on the $\nu_e$ component of the DSNB flux.

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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.078
Threshold uncertainty score0.154

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.094
GPT teacher head0.278
Teacher spread0.184 · 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 designObservational
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
Published2020
Admission routes2
Has abstractyes

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