HerMES: SPIRE galaxy number counts at 250, 350, and 500 <i>μ</i>m
Bibliographic record
Abstract
Emission at far-infrared wavelengths makes up a significant fraction of the total light detected from galaxies over the age of Universe. Herschel provides an opportunity for studying galaxies at the peak wavelength of their emission. Our aim is to provide a benchmark for models of galaxy population evolution and to test pre-existing models of galaxies. With the Herschel Multi-tiered Extra-galactic survey, HerMES, we have observed a number of fields of different areas and sensitivity using the SPIRE instrument on Herschel. We have determined the number counts of galaxies down to ~20 mJy. Our constraints from directly counting galaxies are consistent with, though more precise than, estimates from the BLAST fluctuation analysis. We have found a steep rise in the Euclidean normalised counts <100 mJy. We have directly resolved ~15% of the infrared extra-galactic background at the wavelength near where it peaks.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.026 | 0.015 |
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".