Far-infrared dust properties of highly dust-obscured active galactic nuclei from the AKARI and WISE all-sky surveys
Bibliographic record
Abstract
Abstract The combination of the AKARI and WISE infrared all-sky surveys provides a unique opportunity to identify and characterize the most highly dust-obscured active galactic nuclei (AGNs) in the universe. Dust-obscured AGNs are not easily detectable and are potentially underrepresented in extragalactic surveys due to their high optical extinction, but are readily found in the WISE catalog due to their extremely red mid-infrared (IR) colors. Combining these surveys with photometry from Pan-STARRS and Herschel, we use spectral energy distribution (SED) modeling to characterize the extinction and dust properties of these AGNs. From mid-IR WISE colors we are able to compute bolometric corrections to AGN luminosities. Using AKARI’s far-IR wavelength photometry and broadband AGN/galaxy spectral templates we estimate AGN dust mass and temperature using simple analytic models with three or four parameters. Even without spectroscopic data we can determine a number of AGN dust properties only using SED analysis. These methods, combined with the abundance of archival photometric data publicly available, will be valuable for large-scale studies of dusty, IR-luminous AGNs.
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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 | 0.001 |
| 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) | 0.001 | 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".