An ALMA Survey of the SCUBA-2 Cosmology Legacy Survey UKIDSS/UDS Field: Number Counts of Submillimeter Galaxies
Bibliographic record
Abstract
Abstract We report the first results of AS2UDS, an 870 μm continuum survey with the Atacama Large Millimeter/Submillimeter Array (ALMA) of a total area of ∼50 arcmin2 comprising a complete sample of 716 submillimeter sources drawn from the SCUBA-2 Cosmology Legacy Survey (S2CLS) map of the UKIDSS/UDS field. The S2CLS parent sample covers a 0.96 degree2 field at σ 850 = 0.90 ± 0.05 mJy beam−1. Our deep, high-resolution ALMA observations with σ 870 ∼ 0.25 mJy and a 0.″15–0.″30 FWHM synthesized beam, provide precise locations for 695 submillimeter galaxies (SMGs) responsible for the submillimeter emission corresponding to 606 sources in the low-resolution, single-dish map. We measure the number counts of SMGs brighter than S 870 ≥ 4 mJy, free from the effects of blending and show that the normalization of the counts falls by 28% ± 2% in comparison with the SCUBA-2 published counts, but that the shape remains unchanged. We determine that 44 − 14 + 16 % of the brighter single-dish sources with S 850 ≥ 9 mJy consist of a blend of two or more ALMA-detectable SMGs brighter than S 870 ∼ 1 mJy (corresponding to a galaxy with a total-infrared luminosity of L IR ≳ 1012 L ⊙), in comparison with 28% ± 2% for the single-dish sources at S 850 ≥ 5 mJy. Using the 46 single-dish submillimeter sources that contain two or more ALMA-detected SMGs with photometric redshifts, we show that there is a significant statistical excess of pairs of SMGs with similar redshifts (<1% probability of occurring by chance), suggesting that at least 30% of these blends arise from physically associated pairs of SMGs.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| 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) | 0.003 | 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".