CONTRIBUTION OF LENSED SCUBA GALAXIES TO THE COSMIC INFRARED BACKGROUND
Bibliographic record
Abstract
The surface density of submillimeter (sub-mm) galaxies as a function of flux, usually termed the source number counts, constrains models of the evolution of the density and luminosity of starburst galaxies. At the faint end of the distribution, direct detection and counting of galaxies are not possible. However, gravitational lensing by clusters of galaxies allows detection of sources which would otherwise be too dim to study. We have used the largest catalog of sub-mm-selected sources along the line of sight to galaxy clusters to estimate the faint end of the 850 micron number counts; integrating to S = 0.10 mJy the equivalent flux density at 850 microns is v I_{v} = 0.24 +/- 0.03 nW/m^2/sr. This provides a lower limit to the extragalactic far-infrared background and is consistent with direct estimates of the full intensity from the FIRAS. The results presented here can help to guide strategies for upcoming surveys carried out with single dish sub-mm instruments.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 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".