EVIDENCE FOR A WIDE RANGE OF ULTRAVIOLET OBSCURATION IN<i>z</i>∼ 2 DUSTY GALAXIES FROM THE GOODS-<i>HERSCHEL</i>SURVEY
Bibliographic record
Abstract
Dusty galaxies at z ∼ 2 span a wide range of relative brightness between rest-frame mid-infrared (8 μm) and ultraviolet wavelengths. We attempt to determine the physical mechanism responsible for this diversity. Dust-obscured galaxies (DOGs), which have rest-frame mid-IR to UV flux density ratios ≳ 1000, might be abnormally bright in the mid-IR, perhaps due to prominent emission from active galactic nuclei and/or polycyclic aromatic hydrocarbons, or abnormally faint in the UV. We use far-infrared data from the GOODS- Herschel survey to show that most DOGs with 10 12 L ☉ ≲ L IR ≲ 10 13 L ☉ are not abnormally bright in the mid-IR when compared to other dusty galaxies with similar IR (8–1000 μm) luminosities. We observe a relation between the median IR to UV luminosity ratios and the median UV continuum power-law indices for these galaxies, and we find that only 24% have specific star formation rates that indicate the dominance of compact star-forming regions. This circumstantial evidence supports the idea that the UV- and IR-emitting regions in these galaxies are spatially coincident, which implies a connection between the abnormal UV faintness of DOGs and dust obscuration. We conclude that the range in rest-frame mid-IR to UV flux density ratios spanned by dusty galaxies at z ∼ 2 is due to differing amounts of UV obscuration. Of galaxies with these IR luminosities, DOGs are the most obscured. We attribute differences in UV obscuration to either (1) differences in the degree of alignment between the spatial distributions of dust and massive stars or (2) differences in the total dust content.
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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 | 0.001 |
| 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".