Galaxy properties of type 1 and 2 X-ray selected AGN and a comparison among different classification criteria
Bibliographic record
Abstract
We present analyses of host galaxy properties of type 1 and type 2 X-ray selected Active galactic nuclei (AGNs) in the XMM-XXL field, which have an available optical spectroscopic classification. We modelled their optical to far-infrared spectral energy distributions (SEDs) using the X-CIGALE code. X-CIGALE allows for the fitting of X-ray flux and accounts for the viewing angle of dusty torus and the attenuation from polar dust. By selecting matched type 1 and 2 sub-samples in the X-ray luminosity and redshift parameter space, we find that both types live in galaxies with similar star formation. However, type 2 AGN tend to reside in more massive systems ($ 10.87^{+0.06}_{-0.12}\,M_\odot $) compared to their type 1 counterparts ($ 10.57^{+0.20}_{-0.12}\,M_\odot $). In the second part of our analysis, we compare the spectroscopic classification with that from the SED fitting. X-CIGALE successfully identifies all spectroscopic type 2 sources either by estimating an inclination angle that corresponds to edge on viewing of the source or by measuring increased polar dust in these systems. Approximately 85% of spectroscopic type 1 AGN are also identified as such, based on the SED fitting analysis. There is a small number of sources (∼15% of the sample) that present broad lines in their spectra, but they show strong indications of obscuration, based on SED analysis. These could be systems that are viewed face on and have an extended dust component along the polar direction. The performance of X-CIGALE in classifying AGN is similar at low and high redshifts, under the condition that there is sufficient photometric coverage. Finally, the usage of optical/mid-IR colour criteria to identify optical red AGN (u − W3) suggests that these criteria are better suited for IR selected AGN and their efficiency drops for the low to moderate luminosity sources included in X-ray samples.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".