Is the X-ray bright <i>z</i> = 5.5 quasar SRGE J170245.3+130104 a blazar?
Bibliographic record
Abstract
ABSTRACT Jets may have contributed to promoting the growth of seed black holes in the early Universe, and thus observations of radio-loud high-redshift quasars are crucial to understanding the growth and evolution of the early supermassive black holes. Here we report the radio properties of an X-ray bright z = 5.5 quasar, SRGE J170245.3+130104 (J1702+1301). Our high-resolution radio images reveal the radio counterpart at the optical position of J1702+1301, while another radio component is also detected at ∼23.5 arcsec to the south-west. Our analysis suggests that this south-west component is associated with a foreground galaxy at z ≈ 0.677, which is mixed with J1702+1301 in low-frequency low-resolution radio images. After removing the contamination from this foreground source, we recalculated the radio loudness of J1702+1301 to be R >1100, consistent with those of blazars. J1702+1301 exhibits a flat radio spectrum (α = −0.17 ± 0.05, S ∝ να) between 0.15 and 5 GHz; above 5 GHz, it shows a rising spectrum shape, and the spectral index $\alpha ^{8.2}_{4.7}$ appears to be correlated with the variation of the flux density: in burst states, $\alpha ^{8.2}_{4.7}$ becomes larger. J1702+1301 displays distinct radio variability on time-scales from weeks to years in the source’s rest frame. These radio properties, including high radio loudness, rising spectrum, and rapid variability, tend to support it as a blazar.
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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 | 0.000 |
| 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) | 0.003 | 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".