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Record W2076406066 · doi:10.1086/589506

Discovery of the Radio and X-Ray Counterpart of TeV γ-Ray Source HESS J1731-347

2008· article· en· W2076406066 on OpenAlexaff
W. W. Tian, D. A. Leahy, M. Haverkorn, Biwei Jiang

Bibliographic record

VenueThe Astrophysical Journal · 2008
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Cosmic Phenomena
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsX-rayPhysicsAstrophysicsAstronomyNuclear physics

Abstract

fetched live from OpenAlex

We discover a faint shell-type radio and X-ray source, G353.6-0.7, associated with HESS J1731-347. G353.6-0.7 is likely an old supernova remnant (SNR), based on radio (0.8 GHz, 1.4 GHz and 5 GHz), infrared (8 $\mu$m from the GLIMPSE Legacy Project and 21 $\mu$m from the Midcourse Space Experiment), and X-ray (0.1 keV - 2.4 keV from the ROSAT survey and 5 - 20 keV from the INTEGRAL survey) data. The SNR, centered at ({\sl l}, {\sl b})=(353.55, -0.65) with a radius of $\sim$ 0.25$^{\circ}$, closely matches the outline of the recently discovered extended TeV source HESS J1731-347, which has no previously identified counterpart. A diffuse X-ray enhancement detected in the ROSAT all-sky survey is coincident with lower half shell of the SNR. Therefore the SNR is the best radio counterpart of both the HESS source and the diffuse X-ray enhancement. G353.6-0.7 has an age of $\sim$ 27000 yrs. Altogether, the new discovery provides the best case that an old SNR emits TeV $\gamma$-rays.

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)0.000
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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.007
GPT teacher head0.195
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 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

Citations94
Published2008
Admission routes1
Has abstractyes

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