HerMES: A DEFICIT IN THE SURFACE BRIGHTNESS OF THE COSMIC INFRARED BACKGROUND DUE TO GALAXY CLUSTER GRAVITATIONAL LENSING
Bibliographic record
Abstract
We have observed four massive galaxy clusters with the SPIRE instrument on the Herschel Space Observatory and measure a deficit of surface brightness within their central region after removing detected sources. We simulate the effects of instrumental sensitivity and resolution, the source population, and the lensing effect of the clusters to estimate the shape and amplitude of the deficit. The amplitude of the central deficit is a strong function of the surface density and flux distribution of the background sources. We find that for the current best fitting faint end number counts, and excellent lensing models, the most likely amplitude of the central deficit is the full intensity of the cosmic infrared background (CIB). Our measurement leads to a lower limit to the integrated total intensity of the CIB of MJy sr −1 , with more CIB possible from both low-redshift sources and from sources within the target clusters. It should be possible to observe this effect in existing high angular resolution data at other wavelengths where the CIB is bright, which would allow tests of models of the faint source component of the CIB.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 0.000 |
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".