Co-variability Between the Broad Absorption Lines and Narrow Absorption Lines
Bibliographic record
Abstract
Abstract We investigate the relationship between the variability of broad absorption lines (BALs) or narrow absorption lines (NALs) and that of continuum using a data set of two-epoch SDSS spectra containing 134 C iv NAL-BAL pairs. Our analysis reveals an anti-correlation between the fractional equivalent width (EW) variations in NALs (or BALs) and the fractional flux variations of the continuum, with Spearman rank correlation coefficients of r = −0.47 ( p = 1E-08) and r = −0.58 ( p = 1E-13), respectively. In addition, we find a positive correlation between the fractional EW variations in NALs and BALs ( r = 0.72, p = 1E-22), and derive a regression equation ΔEW NAL /〈EW NAL 〉 = 0.803ΔEW BAL /〈EW BAL 〉 + 0.008, with an intrinsic scatter of 0.14. These results suggest that the variability in the ionizing continuum may play a significant role in the observed changes in C iv NALs and BALs, supporting the idea of photoionization-driven variability. The co-variability between C iv NALs and BALs may imply that they originate from outflows with similar physical conditions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".