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Record W1985768552 · doi:10.1088/0004-637x/777/2/148

SUPERNOVA REMNANT KES 17: AN EFFICIENT COSMIC RAY ACCELERATOR INSIDE A MOLECULAR CLOUD

2013· article· en· W1985768552 on OpenAlexaff
Joseph Gelfand, Daniel Castro, Patrick Slane, Tea Temim, John P. Hughes, Cara E. Rakowski

Bibliographic record

VenueThe Astrophysical Journal · 2013
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Cosmic Phenomena
Canadian institutionsInstitute of Particle Physics
Fundersnot available
KeywordsCosmic rayPhysicsSupernovaAstrophysicsSupernova remnantMolecular cloudAstronomyNear-Earth supernovaAcceleration

Abstract

fetched live from OpenAlex

Supernova remnant Kes 17 (SNR G304.6+0.1) is one of a few but growing number of remnants detected across the electromagnetic spectrum. In this paper, we analyze recent radio, X-ray, and gamma-ray observations of this object, determining that efficient cosmic ray acceleration is required to explain its broadband non-thermal spectrum. These observations also suggest that Kes 17 is expanding inside a molecular cloud, though our determination of its age depends on whether thermal conduction or clump evaporation is primarily responsible for its center-filled thermal X-ray morphology. Evidence for efficient cosmic ray acceleration in Kes 17 supports recent theoretical work that the strong magnetic field, turbulence, and clumpy nature of molecular clouds enhances cosmic ray production in supernova remnants. While additional observations are needed to confirm this interpretation, further study of Kes 17 is important for understanding how cosmic rays are accelerated in supernova remnants.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.682
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.009
GPT teacher head0.220
Teacher spread0.211 · 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.

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

Citations24
Published2013
Admission routes1
Has abstractyes

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