Hunting for metals using XQ-100 Legacy Survey composite spectra
Bibliographic record
Abstract
We investigate the N v absorption signal along the line of sight of background quasars, in order to test the robustness of the use of this ion as the criterion to select intrinsic (i.e. physically related to the quasar host galaxy) narrow absorption lines (NALs). We build composite spectra from a sample of ∼ 1000 C iv absorbers, covering the redshift range 2.55 < z < 4.73, identified in 100 individual sight lines from the XQ-100 Legacy Survey. We detect a statistically significant N v absorption signal only within 5000 km s−1 of the systemic redshift, |$z_{\rm em}$|. This absorption trough is ∼ 15σ when only C iv systems with N(C iv) > 1014 cm−2 are included in the composite spectrum. This result confirms that N v offers an excellent statistical tool to identify intrinsic systems. We exploit stacks of 11 different ions to show that the gas in proximity to a quasar exhibits a considerably different ionization state with respect to gas in the transverse direction and intervening gas at large velocity separations from the continuum source. Indeed, we find a dearth of cool gas, as traced by low-ionization species and in particular by Mg ii, in the proximity of the quasar. We compare our findings with the predictions given by a range of cloudy ionization models and find that they can be naturally explained by ionization effects of the quasar.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".