Exploring the Spectral Energy Distributions of Luminous Broad Absorption Line Quasars at High Redshift
Bibliographic record
Abstract
Abstract We present the multiwavelength spectral energy distributions (SEDs) for 65 luminous broad absorption line (BAL) quasars with redshifts 1.55 ≲ z ≲ 3.50 from the Gemini Near Infrared Spectrograph–Distant Quasar Survey (GNIRS-DQS). We integrate data from a variety of ground- and space-based observatories to construct a comprehensive spectral profile of these objects from radio through X-rays. In addition, we present a mid-infrared to X-ray composite SED of these sources. Our data set represents the most uniform sample of BAL quasars, providing a statistically robust set of SEDs. Our findings indicate that the BAL quasars in the GNIRS-DQS sample exhibit significant reddening in the ultraviolet-optical continuum relative to their non-BAL counterparts, consistent with previous studies. Notably, our analysis reveals no significant differences in the mid- or near-infrared spectral regime between BAL and non-BAL quasars. In line with previous work, we find no strong evidence that BAL and non-BAL quasars possess fundamentally different SEDs, also consistent with recent findings that both groups display similar rest-frame optical emission-line properties.
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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 | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".