ERQs are the BOSS of quasar samples: the highest velocity [O iii] quasar outflows
Bibliographic record
Abstract
ABSTRACT We investigate extremely red quasars (ERQs), a remarkable population of heavily reddened quasars at redshift z ∼ 2−3 that might be caught during a short-lived ‘blow-out’ phase of quasar/galaxy evolution. We perform a near-IR observational campaign using Keck/NIRSPEC, VLT/X-shooter, and Gemini/GNIRS to measure rest-frame optical spectra of 28 ERQs with median infrared luminosity 〈log L(erg s−1)〉 ∼ 46.2. They exhibit the broadest and most blueshifted [O iii] λ4959,5007 emission lines ever reported, with widths (w90) ranging between 2053 and 7227 km s−1, and maximum outflow speeds (v98) up to 6702 km s−1. ERQs on average have [O iii] outflows velocities about three times larger than those of luminosity-matched blue quasar samples. This discrepancy can be explained by a strong correlation between [O iii] kinematics and i–W3 colour, and not by radio loudness, or higher Eddington ratios. We estimate for these objects that at least 3–5 per cent of their bolometric luminosity is being converted into the kinetic power of the observed wind. Our results reveal that ERQs have the potential to strongly affect the evolution of host galaxies.
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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 | 0.000 |
| 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".