Dust-obscured Galaxies with Broken Power-law Spectral Energy Distributions Discovered by UNIONS
Bibliographic record
Abstract
Abstract We report on the spectral energy distributions (SEDs) of infrared (IR)-bright dust-obscured galaxies (DOGs) with (i − [22])AB ≥ 7.0. Using photometry from the deep and wide Ultraviolet Near-Infrared Optical Northern Survey, combined with near-IR (NIR) and mid-IR data from the UKIRT Infrared Deep Sky Survey and the Wide-field Infrared Survey Explorer, we successfully identified 382 DOGs in ∼170 deg2. Among them, the vast majority (376 DOGs) were classified into two subclasses: bump DOGs (132/376) and power-law (PL) DOGs (244/376), which are dominated by star formation and active galactic nuclei (AGNs), respectively. Through the SED analysis, we find that roughly half (120/244) of the PL DOGs show broken power-law (BPL) SEDs. The significant red slope from optical to NIR in the SEDs of these “BPL DOGs” probably reflects their large amount of dust extinction. In other words, BPL DOGs are more heavily obscured AGNs, compared to PL DOGs with non-BPL SEDs.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".