An ASKAP survey for H i absorption towards dust-obscured quasars
Bibliographic record
Abstract
ABSTRACT Obscuration of quasars by accreted gas and dust, or dusty intervening galaxies, can cause active galactic nuclei (AGN) to be missed in optically selected surveys. Radio observations can overcome this dust bias. In particular, radio surveys searching for H i absorption inform us on how the AGN can impact on the cold neutral gas medium within the host galaxy, or the population of intervening galaxies through the observed line of sight gas kinematics. We present the results of an H i absorption line survey at 0.4 < z < 1 towards 34 obscured quasars with the Australian SKA Pathfinder (ASKAP) commissioning array. We detect three H i absorption lines, with one of these systems previously unknown. Through optical follow-up for two sources, we find that in all detections the H i gas is associated with the AGN, and hence that these AGN are obscured by material within their host galaxies. Most of our sample are compact, and in addition, are either gigahertz peaked spectrum (GPS), or steep spectrum (CSS) sources, both thought to represent young or recently re-triggered radio AGN. The radio spectral energy distribution classifications for our sample agree with galaxy evolution models in which the obscured AGN has only recently become active. Our associated H i detection rate for GPS and compact SS sources matches those of other surveys towards such sources. We also find shallow and asymmetric H i absorption features, which agrees with previous findings that the cold neutral medium in compact radio galaxies is typically kinematically disturbed by the AGN.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".