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Record W4308356054 · doi:10.1088/1361-6471/aca03b

A test of spatial coincidence between CHIME FRBs and IceCube TeV energy neutrinos

2022· article· en· W4308356054 on OpenAlexaboutno aff
S. Desai

Bibliographic record

VenueJournal of Physics G Nuclear and Particle Physics · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Cosmic Phenomena
Canadian institutionsnot available
Fundersnot available
KeywordsCoincidenceNeutrinoPhysicsParticle physicsAstrophysicsAstronomyNuclear physicsMedicine

Abstract

fetched live from OpenAlex

Abstract We search for a spatial association between the Canadian Hydrogen Mapping Intensity Experiment (CHIME) FRBs and IceCube neutrinos detected in the TeV energy range, by counting the total number of neutrino-FRB pairs with angular separations of <3 degrees, as well as within the observed neutrino error circle. This number constitutes the total signal events, which is then compared to the total background, corresponding to the null hypothesis of no spatial association. The background was obtained from the total neutrino-FRB matches in off-source angular windows with the same solid angle as the signal window. We do not find any statistically significant excess compared to the background. Therefore, we conclude that there is no evidence for an angular correlation between the IceCube neutrinos in the TeV energy range and CHIME FRBs. For each of these searches, we report 90% Bayesian credible interval upper limits on the observed FRB-induced neutrinos.

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)0.006
metaresearch head score (Gemma)0.038
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 score0.061
Threshold uncertainty score0.122

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.038
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.011
GPT teacher head0.213
Teacher spread0.202 · 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

Citations4
Published2022
Admission routes1
Has abstractyes

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