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Record W2785565279 · doi:10.3847/2041-8213/aabaca

Search for Neutrinos in Super-Kamiokande Associated with the GW170817 Neutron-star Merger

2018· article· en· W2785565279 on OpenAlexaff

Bibliographic record

VenueThe Astrophysical Journal Letters · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGamma-ray bursts and supernovae
Canadian institutionsUniversity of ReginaUniversity of British ColumbiaTRIUMFUniversity of Toronto
FundersScience and Technology Facilities Council
KeywordsNeutrinoMeasurements of neutrino speedGravitational waveMuonNeutrino detectorMuon neutrinoNeutrino oscillationSolar neutrino problem

Abstract

fetched live from OpenAlex

Abstract We report the results of a neutrino search in Super-Kamiokande (SK) for coincident signals with the first detected gravitational wave (GW) produced by a binary neutron-star merger, GW170817, which was followed by a short gamma-ray burst, GRB170817A, and a kilonova/macronova. We searched for coincident neutrino events in the range from 3.5 MeV to ∼100 PeV, in a time window ±500 s around the gravitational wave detection time, as well as during a 14-day period after the detection. No significant neutrino signal was observed for either time window. We calculated 90% confidence level upper limits on the neutrino fluence for GW170817. From the upward-going-muon events in the energy region above 1.6 GeV, the neutrino fluence limit is 16.0 − 0.6 + 0.7 ( 21.3 − 0.8 + 1.1 ) cm−2 for muon neutrinos (muon antineutrinos), with an error range of ±5° around the zenith angle of NGC4993, and the energy spectrum is under the assumption of an index of −2. The fluence limit for neutrino energies less than 100 MeV, for which the emission mechanism would be different than for higher-energy neutrinos, is also calculated. It is 6.6 × 107 cm−2 for anti-electron neutrinos under the assumption of a Fermi–Dirac spectrum with average energy of 20 MeV.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.236
Teacher spread0.223 · 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

Citations37
Published2018
Admission routes1
Has abstractyes

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