IGR J18249-3243: a new GeV-emitting FR II and the emerging population of high energy radio galaxies
Bibliographic record
Abstract
The advent of new all-sky radio surveys such as the VLA Sky Survey (VLASS) and the Rapid ASKAP Continuum Survey (RACS), performed with the latest generation radio telescopes, is opening new possibilities on the classification and study of extragalactic $\gamma$-ray sources, specially the underrepresented ones like radio galaxies. In particular, the enhanced sensitivity (sub-mJy level) and resolution (a few arcsec) provides a better morphological and spectral classification. In this work, we present the reclassification of a Fermi-LAT source as a new FRII radio galaxy from the INTEGRAL sample found to emit at GeV energies. Through a broad-band spectral fitting from radio to $\gamma$-ray, we find that the commonly invoked jet contribution is not sufficient to account for the observed $\gamma$-ray flux. Our modeling suggests that the observed emission could mainly originate in the lobes (rather than in the radio core) by inverse Compton scattering of radio-emitting electrons off the ambient photon fields. In addition, we cross-correlated the latest generation radio surveys with a list of Fermi-LAT objects from the literature considered to be candidate misaligned AGN, finding four new radio galaxies with a double-lobed morphology. Additional four objects could be classified as such thanks to previous studies in the literature, for a total of nine new radio galaxies with GeV emission presented in this work. We foresee that further objects of this class might be found in the near future with the advent of the Square Kilometer Array (SKA), populating the GeV sky.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".