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Record W2767665651 · doi:10.1093/mnrasl/slx180

Radio emission from the X-ray pulsar Her X-1: a jet launched by a strong magnetic field neutron star?

2017· article· en· W2767665651 on OpenAlexaff
J. van den Eijnden, N. Degenaar, J. C. A. Miller‐Jones, R. Wijnands, J. M. Mïller, A. L. King, M. P. Rupen

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society Letters · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysical Phenomena and Observations
Canadian institutionsHerzberg Institute of Astrophysics
Fundersnot available
KeywordsPhysicsAstrophysicsNeutron starPulsarX-ray binaryJet (fluid)AstronomyMagnetic fieldX-ray pulsarAccretion (finance)

Abstract

fetched live from OpenAlex

Abstract Her X-1 is an accreting neutron star (NS) in an intermediate-mass X-ray binary. Like low-mass X-ray binaries (LMXBs), it accretes via Roche lobe overflow, but similar to many high-mass X-ray binaries containing a NS; Her X-1 has a strong magnetic field and slow spin. Here, we present the discovery of radio emission from Her X-1 with the Very Large Array. During the radio observation, the central X-ray source was partially obscured by a warped disc. We measure a radio flux density of 38.7 ± 4.8 μJy at 9 GHz but cannot constrain the spectral shape. We discuss possible origins of the radio emission, and conclude that coherent emission, a stellar wind, shocks and a propeller outflow are all unlikely explanations. A jet, as seen in LMXBs, is consistent with the observed radio properties. We consider the implications of the presence of a jet in Her X-1 on jet formation mechanisms and on the launching of jets by NSs with strong magnetic fields.

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 score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.206
Teacher spread0.198 · 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

Citations17
Published2017
Admission routes1
Has abstractyes

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