AGN UNIFICATION AT<i>z</i>∼ 1:<i>u</i>–<i>R</i>COLORS AND GRADIENTS IN X-RAY AGN HOSTS
Bibliographic record
Abstract
We present uncontaminated rest-frame u − R colors of 78 X-ray-selected active galactic nucleus (AGN) hosts at 0.5 < z < 1.5 in the Chandra Deep Fields measured with Hubble Space Telescope ( HST )/Advanced Camera for Surveys/NICMOS and Very Large Telescope/ISAAC imaging. We also present spatially resolved NUV − R color gradients for a subsample of AGN hosts imaged by HST /Wide Field Camera 3 (WFC3). Integrated, uncorrected photometry is not reliable for comparing the mean properties of soft and hard AGN host galaxies at z ∼ 1 due to color contamination from point-source AGN emission. We use a cloning simulation to develop a calibration between concentration and this color contamination and use this to correct host galaxy colors. The mean u − R color of the unobscured/soft hosts beyond ∼6 kpc is statistically equivalent to that of the obscured/hard hosts (the soft sources are 0.09 ± 0.16 mag bluer). Furthermore, the rest-frame V − J colors of the obscured and unobscured hosts beyond ∼6 kpc are statistically equivalent, suggesting that the two populations have similar distributions of dust extinction. For the WFC3/infrared sample, the mean NUV − R color gradients of unobscured and obscured sources differ by less than ∼0.5 mag for r > 1.1 kpc. These three observations imply that AGN obscuration is uncorrelated with the star formation rate beyond ∼1 kpc. These observations favor a unification scenario for intermediate-luminosity AGNs in which obscuration is determined geometrically. Scenarios in which the majority of intermediate-luminosity AGNs at z ∼ 1 are undergoing rapid, galaxy-wide quenching due to AGN-driven feedback processes are disfavored.
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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".