C IV BROAD ABSORPTION LINE ACCELERATION IN SLOAN DIGITAL SKY SURVEY QUASARS
Bibliographic record
Abstract
ABSTRACT We present results from the largest systematic investigation of broad absorption line (BAL) acceleration to date. We use spectra of 140 quasars from three Sloan Digital Sky Survey programs to search for global velocity offsets in BALs over timescales of ≈2.5–5.5 years in the quasar rest frame. We carefully select acceleration candidates by requiring monolithic velocity shifts over the entire BAL trough, avoiding BALs with velocity shifts that might be caused by profile variability. The C iv BALs of two quasars show velocity shifts consistent with the expected signatures of BAL acceleration, and the BAL of one quasar shows a velocity-shift signature of deceleration. In our two acceleration candidates, we see evidence that the magnitude of the acceleration is not constant over time; the magnitudes of the change in acceleration for both acceleration candidates are difficult to produce with a standard disk-wind model or via geometric projection effects. We measure upper limits to acceleration and deceleration for 76 additional BAL troughs and find that the majority of BALs are stable to within about 3% of their mean velocities. The lack of widespread acceleration/deceleration could indicate that the gas producing most BALs is located at large radii from the central black hole and/or is not currently strongly interacting with ambient material within the host galaxy along our line of sight.
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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 | 0.003 | 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) | 0.001 | 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".