Metal enrichment and evolution in four z > 6.5 quasar sightlines observed with JWST/NIRSpec
Bibliographic record
Abstract
We present JWST/NIRSpec R~2700 spectra of four high-redshift quasars: VDES J0020-3653 (z = 6.860), DELS J0411-0907 (z = 6.825), UHS J0439+1634 (z = 6.519) and ULAS J1342+0928 (z = 7.535). The exquisite data quality, signal-to-noise ratio of 50-200, and large $0.86\!~μ{\rm m}\le λ\le 5.5\!~μ{\rm m}$ spectral coverage allows us to identify between 13 and 17 intervening and proximate metal absorption line systems in each quasar spectrum, with a total number of 61 absorption-line systems detected at 2.426 and find: i) A continued increase of the low-ionization OI, CII, and SiII incidence, ii) Decreasing high-ionization CIV and SiIV incidence with a transition from predominantly high- to low-ionization at $z\approx6.0$, and iii) a constant MgII incidence across all redshifts. The observations support a change in the ionization state of the intergalactic medium in the EoR rather than a change in metallicity. The abundance ratio of [Si/O] in five z>6 absorption systems show enrichment signatures produced by low-mass Pop III pair instability supernovae, and possibly Pop III hypernovae. In the Gunn-Peterson troughs we detect transmission spikes where Ly$α$ photons can escape. From 22 absorption systems at z>5.7, only a single low-ionization system out of 13 lies within 2000 km/s from a spike, while four high-ionization systems out of nine lie within ~2000 km/s from a spike. This confirms that galaxies responsible for the heavy elements that are transported into the circumgalactic medium lie in predominantly in high-density, neutral environments, while lower density environments are ionized without being polluted by metals at $z\approx$ 6-7. [abridged]
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".