JADES: nitrogen enhancement in high-redshift broad-line active galactic nuclei
Bibliographic record
Abstract
ABSTRACT The unexpectedly high nitrogen-to-oxygen (N/O) ratios observed in high-redshift (z) galaxies have challenged our understanding of early star formation. Notably, many of these nitrogen-rich galaxies show signatures of active galactic nuclei (AGNs), suggesting a possible connection between black hole formation and nitrogen enrichment. To explore this connection, we analyse stacked spectra of $z=4{\!-\!}7$ broad-line and narrow-line AGNs using deep Near Infrared Spectrograph data from the JWST Advanced Deep Extragalactic Survey. We identify a significant N iii] quintuplet and a high electron density (${\sim} 10^{4}$ cm$^{-3}$) only in the broad-line AGN stack, indicating nitrogen-rich ($\log (\mathrm{N/C})\simeq 0.5$, $\log (\mathrm{N/O})>-0.6$) and dense gas similar to the high-z nitrogen-rich galaxies. Our findings suggest that dense nuclear star formation may trap nitrogen-rich gas in proto-globular clusters, in line with the high N/O observed in local globular clusters; associated runaway stellar collisions could produce intermediate-mass black hole seeds, as predicted by some models and simulations, whose accretion results into AGN signatures. These findings support scenarios connecting the early black hole seeding and growth to merging processes within and between proto-globular clusters in primeval galaxies.
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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 | 0.000 | 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".