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Record W2984447553 · doi:10.3847/1538-4357/ab4ae2

Search for Sources of Astrophysical Neutrinos Using Seven Years of IceCube Cascade Events

2019· article· en· W2984447553 on OpenAlexaff

Bibliographic record

VenueThe Astrophysical Journal · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Cosmic Phenomena
Canadian institutionsUniversity of AlbertaSnolab
FundersScience and Technology Facilities Council
KeywordsNeutrinoSkyCascadeMuonContext (archaeology)Neutrino detectorMuon neutrinoNeutrino astronomy

Abstract

fetched live from OpenAlex

Abstract Low-background searches for astrophysical neutrino sources anywhere in the sky can be performed using cascade events induced by neutrinos of all flavors interacting in IceCube with energies as low as ∼1 TeV. Previously we showed that, even with just two years of data, the resulting sensitivity to sources in the southern sky is competitive with IceCube and ANTARES analyses using muon tracks induced by charge current muon neutrino interactions—especially if the neutrino emission follows a soft energy spectrum or originates from an extended angular region. Here, we extend that work by adding five more years of data, significantly improving the cascade angular resolution, and including tests for point-like or diffuse Galactic emission to which this data set is particularly well suited. For many of the signal candidates considered, this analysis is the most sensitive of any experiment to date. No significant clustering was observed, and thus many of the resulting constraints are the most stringent to date. In this paper we will describe the improvements introduced in this analysis and discuss our results in the context of other recent work in neutrino astronomy.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.345
Threshold uncertainty score0.701

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.016
GPT teacher head0.259
Teacher spread0.243 · 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 teacher head, 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

Citations84
Published2019
Admission routes1
Has abstractyes

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