GA-NIFS: A massive black hole in a low-metallicity AGN at $z\sim5.55$ revealed by JWST/NIRSpec IFS
Bibliographic record
Abstract
We present JWST/NIRSpec Integral Field Spectrograph rest-frame optical data of the compact $z=5.55$ galaxy GS_3073. Its prominent broad components in several hydrogen and helium lines (while absent in the forbidden lines), and the detection of a large equivalent width of He II$\lambda4686$, EW(He II) ~ 20A, unambiguously identify it as an active galactic nucleus (AGN). We measure a gas-phase metallicity of $Z_{\rm gas}/Z_\odot\sim0.21^{+0.08}_{-0.04}$, lower than what has been inferred for both more luminous AGN at similar redshift and lower redshift AGN. We empirically show that classical emission line ratio diagnostic diagrams cannot be used to distinguish between the primary ionisation source (AGN or star formation) for such low-metallicity systems, whereas different diagnostic diagrams involving He II$\lambda4686$ prove very useful, independent of metallicity. We measure the central black hole mass to be $\log(M_{\rm BH}/M_\odot)\sim8.2\pm0.4$ based on the luminosity and width of the broad line region of the H$α$ emission. While this places GS_3073 at the lower end of known high-redshift black hole masses, it still appears to be over-massive compared to its host galaxy properties. We detect an outflow with projected velocity $\gtrsim700$ km/s and infer an ionised gas mass outflow rate of about $100\ M_\odot/$yr, suggesting that GS_3073 is able to enrich the intergalactic medium with metals one billion years after the Big Bang.
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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".