JADES – the Rosetta stone of <i>JWST</i>-discovered AGN: deciphering the intriguing nature of early AGN
Bibliographic record
Abstract
ABSTRACT JWST has discovered a large population of active galactic nuclei (AGN) at high redshift, which are weak in the X-rays. Here we present the NIRSpec spectrum of the most extreme of these objects, GN-28074, an AGN at $z=2.26$ with prominent hydrogen and He i broad lines, and with the highest limit on the bolometric to X-ray luminosity ratio among all spectroscopically confirmed AGN in GOODS. This source is also characterized by a mid-IR excess, likely associated with the AGN torus’ hot dust. The high bolometric luminosity and moderate redshift of this AGN allow us to explore its properties more in depth relative to other JWST-discovered AGN. The NIRSpec spectrum reveals prominent, slightly blueshifted absorption of H$\alpha$, H$\beta$, and He i $\lambda$10830. The Balmer absorption lines require gas with densities of $n_{\rm H}\gt 10^8~{\rm cm}^{-3}$, consistent with clouds in the broad-line region (BLR). This finding suggests that part of the X-ray weakness is due to high (Compton-thick) X-ray absorption by clouds in the BLR, or in its outer regions. GN-28074 is also extremely radio-weak. The radio weakness can also be explained in terms of absorption, as the inferred density of the BLR clouds makes them attenuate the radio emission through free–free absorption. Alternatively, the nuclear magnetic field may be underdeveloped, resulting both in intrinsically weak radio emission and lack of hot corona, hence intrinsic X-ray weakness. Finally, we show that recently proposed scenarios, invoking hyper-dense outflows or Raman scattering to explain the broad H$\alpha$, are ruled out.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".