The SCUBA-2 Cosmology Legacy Survey: blank-field number counts of 450-mu m-selected galaxies and their contribution to the cosmic infrared background
Bibliographic record
Abstract
The first deep blank-field 450 μm map (1σ ≈ 1.3 mJy) from the Submillimetre Common-User Bolometer Array-2 SCUBA-2 Cosmology Legacy Survey (S2CLS), conducted with the James Clerk Maxwell Telescope (JCMT) is presented. Our map covers 140 arcmin[Superscript: 2] of the Cosmological Evolution Survey field, in the footprint of the Hubble Space Telescope (HST) Cosmic Assembly Near-Infrared Deep Extragalactic Legacy Survey. Using 60 submillimetre galaxies detected at ≥3.75σ, we evaluate the number counts of 450-μm-selected galaxies with flux densities S[Subscript: 450] > 5 mJy. The 8 arcsec JCMT beam and high sensitivity of SCUBA-2 now make it possible to directly resolve a larger fraction of the cosmic infrared background (CIB, peaking at λ ∼ 200 μm) into the individual galaxies responsible for its emission than has previously been possible at this wavelength. At S[Subscript: 450] > 5 mJy, we resolve (7.4 ± 0.7) × 10[Superscript: −2] MJy sr[Superscript: −1] of the CIB at 450 μm (equivalent to 16 ± 7 per cent of the absolute brightness measured by the Cosmic Background Explorer at this wavelength) into point sources. A further ∼40 per cent of the CIB can be recovered through a statistical stack of 24 μm emitters in this field, indicating that the majority (≈60 per cent) of the CIB at 450 μm is emitted by galaxies with S[Superscript: 450] > 2 mJy. The average redshift of 450 μm emitters identified with an optical/near-infrared counterpart is estimated to be 〈z〉 = 1.3, implying that the galaxies in the sample are in the ultraluminous class (LIR≈1.1×10[Superscript: 12]L⊙LIR≈1.1×10[Superscript: 12]L[Subscript: ⊙]). If the galaxies contributing to the statistical stack lie at similar redshifts, then the majority of the CIB at 450 μm is emitted by galaxies in the luminous infrared galaxy (LIRG) class with L[Subscript: IR] > 3.6 × 10[Superscript: 11] L[Subscript: ⊙].
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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 | 0.004 | 0.003 |
| 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) | 0.004 | 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".