Ionization-driven intrinsic absorption line variability of BAL quasars in the Stripe 82 region
Bibliographic record
Abstract
Abstract We investigate the connection between the intrinsic C iv absorption line variability and the continuum flux changes of broad absorption line (BAL) quasars using a sample of 78 sources in the Stripe 82 region. The absorption trough variability parameters are measured using the archival multi-epoch spectroscopic data from the Sloan Digital Sky Survey (SDSS), and the continuum flux variability parameters are estimated from the photometric light curves obtained by the SDSS and the Catalina Real-Time Survey surveys. We find evidence for weak correlations (ρs ∼ 0.3) between the intrinsic C iv absorption line variability and the quasar continuum variability for the final sample of 78 BAL quasars. The correlation strengths improve (ρs ∼ 0.5) for the ‘high-signal-to-noise ratio (SNR)’ sample sources that have higher spectral SNR. Using two subsets of the high-SNR sample differing on the absorption trough depth, we find that the shallow-trough subset shows an even stronger correlation (ρs ∼ 0.6), whereas the deep-trough subset does not show any correlation between the absorption line variability and the continuum variability. These results point to the important role of saturation effects in the correlation between the absorption line variability and the continuum variability of BAL quasars. Considering other effects that can also smear the correlation, we conclude that the actual correlation between the absorption line and continuum variability is even stronger.
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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 | 0.001 | 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) | 0.001 | 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".