Characterization of a sample of γ-ray active galactic nuclei
Bibliographic record
Abstract
ABSTRACT We analyse 77 Fermi sources and their potential low-energy counterparts previously proposed in the literature. These sources were classified as active galactic nuclei (AGNs), mainly blazars, based on optical spectroscopy. The main goals of this work are to examine these associations, classify the blazars based on their multiwavelength spectral energy distributions (SEDs), and identify potential masquerading BL Lac objects. Through SED analysis, we assess whether the multiwavelength emission follows the characteristic double-peaked curve of blazars. Additionally, we propose the region of origin of the emission at different wavelengths, investigate the correlation between $\gamma$-ray and lower energy emission, and classify objects as low-, intermediate-, high-, or extreme high-synchrotron peaked (LSP, ISP, HSP, E-HSP) blazars. We search for masquerading BL Lacs, a class of flat-spectrum radio quasars where broad emission lines are swamped by non-thermal jet emission. The multiwavelength analysis revealed that the 64 radio-loud sources in our sample exhibit an SED with a double-peaked structure, typically ascribed to jet activity. Based on the synchrotron peak, 46 are HSP, 11 are ISP, and seven are LSP. We also found 9–18 masquerading BL Lac candidates ($\approx$15–30 per cent of the radio-loud sample). For the 13 radio-quiet unassociated gamma-ray sources, the SEDs do not exhibit the double-peaked structure typical of jetted AGNs. Further analysis ruled out star formation as the origin of the observed $\gamma$-ray emission, making its reconciliation with lower energy emission challenging. We explored alternative counterparts, identifying low-energy matches for seven sources, with no plausible counterparts found for the others.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 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".