SCUBA-2 Ultra Deep Imaging EAO Survey (STUDIES). V. Confusion-limited Submillimeter Galaxy Number Counts at 450 μm and Data Release for the COSMOS Field
Bibliographic record
Abstract
Abstract We present confusion-limited SCUBA-2 450 μm observations in the COSMOS-CANDELS region as part of the James Clerk Maxwell Telescope Large Program SCUBA-2 Ultra Deep Imaging EAO Survey. Our maps at 450 and 850 μm cover an area of 450 arcmin2. We achieved instrumental noise levels of σ 450 = 0.59 mJy beam−1 and σ 850 = 0.09 mJy beam−1 in the deepest area of each map. The corresponding confusion noise levels are estimated to be 0.65 and 0.36 mJy beam−1. Above the 4σ (3.5σ) threshold, we detected 360 (479) sources at 450 μm and 237 (314) sources at 850 μm. We derive the deepest blank-field number counts at 450 μm, covering the flux-density range of 2–43 mJy. These are in agreement with other SCUBA-2 blank-field and lensing-cluster observations but are lower than various model counts. We compare the counts with those in other fields and find that the field-to-field variance observed at 450 μm at the R = 6 ′ scale is consistent with Poisson noise, so there is no evidence of strong 2D clustering at this scale. Additionally, we derive the integrated surface brightness at 450 μm down to 2.1 mJy to be 57.3 − 6.2 + 1.0 Jy deg−2, contributing to 41% ± 4% of the 450 μm extragalactic background light (EBL) measured by Cosmic Background Explorer and Planck. Our results suggest that the 450 μm EBL may be fully resolved at 0.08 − 0.08 + 0.09 mJy, which extremely deep lensing-cluster observations and next-generation submillimeter instruments with large aperture sizes may be able to achieve.
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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 | 0.002 |
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".