Chemical abundances in Seyfert galaxies – X. Sulphur abundance estimates
Bibliographic record
Abstract
ABSTRACT For the first time, the sulphur abundance relative to hydrogen (S/H) in the narrow-line regions of a sample of Seyfert 2 nuclei (Sy 2s) has been derived via direct estimation of the electron temperature. Narrow emission-line intensities from the Sloan Digital Sky Survey (SDSS) Data Release 17 (DR17) [in the wavelength range 3000 < λ(Å) < 9100] and from the literature for a sample of 45 nearby (z < 0.08) Sy 2s were considered. Our direct estimates indicate that Sy 2s have similar temperatures in the gas region where most of the $\rm S\rm ^{+}$ ions are located in comparison with that of star-forming regions (SFs). However, Sy 2s present higher temperature values (${\sim} 10\, 000$ K) in the region where most of the $\rm S\rm ^{2+}$ ions are located relative to that of SFs. We derive the total sulphur abundance in the range of $6.2 \: \lesssim 12+\log (\rm S/H) \: \lesssim \: 7.5$, corresponding to 0.1–1.8 times the solar value. These sulphur abundance values are lower by ∼0.4 dex than those derived in SFs with similar metallicity, indicating a distinct chemical enrichment of the interstellar medium (ISM) for these object classes. The sulphur abundance relative to oxygen (S/O) values for our Sy 2 sample present an abrupt (∼0.5 dex) decrease with increasing oxygen abundance relative to hydrogen (O/H) for the high-metallicity regime [$\rm 12+\log (O/H) \: \gtrsim 8.7)$], what is not seen for the SFs. However, when our Sy 2 estimates are combined with those from a large sample of SFs, we did not find any dependence between S/O and O/H.
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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 | 0.002 | 0.001 |
| 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) | 0.002 | 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".