HerMES: THE FAR-INFRARED EMISSION FROM DUST-OBSCURED GALAXIES
Bibliographic record
Abstract
Dust-obscured galaxies (DOGs) are an ultraviolet-faint, infrared-bright galaxy population that reside at z ∼ 2 and are believed to be in a phase of dusty star-forming and active galactic nucleus (AGN) activity. We present far-infrared (far-IR) observations of a complete sample of DOGs in the 2 deg 2 of the Cosmic Evolution Survey. The 3077 DOGs have 〈 z 〉 = 1.9 ± 0.3 and are selected from 24 μm and r + observations using a color cut of r + − [24] ⩾ 7.5 (AB mag) and S 24 ⩾ 100 μJy. Based on the near-IR spectral energy distributions, 47% are bump DOGs (star formation dominated) and 10% are power-law DOGs (AGN-dominated). We use SPIRE far-IR photometry from the Herschel Multi-tiered Extragalactic Survey to calculate the IR luminosity and characteristic dust temperature for the 1572 (51%) DOGs that are detected at 250 μm (⩾3σ). For the remaining 1505 (49%) that are undetected, we perform a median stacking analysis to probe fainter luminosities. Herschel -detected and undetected DOGs have average luminosities of (2.8 ± 0.4) × 10 12 L ☉ and (0.77 ± 0.08) × 10 12 L ☉ , and dust temperatures of (33 ± 7) K and (37 ± 5) K, respectively. The IR luminosity function for DOGs with S 24 ⩾ 100 μJy is calculated, using far-IR observations and stacking. DOGs contribute 10%–30% to the total star formation rate (SFR) density of the universe at z = 1.5–2.5, dominated by 250 μm detected and bump DOGs. For comparison, DOGs contribute 30% to the SFR density for all z = 1.5–2.5 galaxies with S 24 ⩾ 100 μJy. DOGs have a large scatter about the star formation main sequence and their specific SFRs show that the observed phase of star formation could be responsible for their total observed stellar mass at z ∼ 2.
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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 | 0.000 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".