Bibliographic record
Abstract
Extreme high-synchrotron-peak blazars (EHSPs) are postulated as the most efficient and extreme particle accelerators in the universe but remain enigmatic as a possible new class of TeV gamma-ray blazars. Blazars are active galactic nuclei (AGNs) with jets of relativistic particles that generate non-thermal emission pointed along the line-of-sight. Their spectral energy distribution (SED) are characterized by synchrotron and inverse-Compton peaks, indicating acceleration of leptonic and possibly hadronic particle populations in the jet. EHSPs are characterized by a peak synchrotron frequency $>10^{17}{Hz}$ with their Compton peak expected to fall in the TeV range. Indeed, the handful of EHSPs detected by Imaging Air Cherenkov Telescopes (IACTs) have presented challenges where some may be a high-frequency extension of the blazar sequence while others peaking around 10 TeV may represent a different class of TeV emitters. Detections of the high-energy and very-high-energy (HE; E > 100 MeV, VHE; E > 100 GeV) components of the Compton peak will play an important role in constraining the acceleration model derived from the SED. We present the discovery of TeV emission from RBS 1366, a candidate EHSP, by the VERITAS observatory. Using HE and VHE data from the \fermi and VERITAS observatories, respectively, we characterize the detection by providing an SED and model fit in the context of other EHSP candidates. Our work confirms the status of RBS 1366 as an EHBL.
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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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
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".