Comparing emission- and absorption-based gas-phase metallicities in GRB host galaxies at <i>z</i> = 2−4 using JWST
Bibliographic record
Abstract
ABSTRACT Much of what is known of the chemical composition of the universe is based on emission line spectra from star-forming galaxies. Emission-based inferences are, nevertheless, model-dependent and they are dominated by light from luminous star-forming regions. An alternative and sensitive probe of the metallicity of galaxies is through absorption lines imprinted on the luminous afterglow spectra of long gamma ray bursts (GRBs) from neutral material within their host galaxy. We present results from a JWST/NIRSpec programme to investigate for the first time the relation between the metallicity of neutral gas probed in absorption by GRB afterglows and the metallicity of the star-forming regions for the same host galaxy sample. Using an initial sample of eight GRB host galaxies at z = 2.1–4.7, we find a tight relation between absorption and emission line metallicities when using the recently proposed $\hat{R}$ metallicity diagnostic (±0.2 dex). This agreement implies a relatively chemically homogeneous multiphase interstellar medium and indicates that absorption and emission line probes can be directly compared. However, the relation is less clear when using other diagnostics, such as R23 and R3. We also find possible evidence of an elevated N/O ratio in the host galaxy of GRB 090323 at z = 4.7, consistent with what has been seen in other z > 4 galaxies. Ultimate confirmation of an enhanced N/O ratio and of the relation between absorption and emission line metallicities will require a more direct determination of the emission line metallicity via the detection of temperature-sensitive auroral lines in our GRB host galaxy sample.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".