BLAST: RESOLVING THE COSMIC SUBMILLIMETER BACKGROUND
Bibliographic record
Abstract
The Balloon-borne Large Aperture Submillimeter Telescope (BLAST) has made 1 deg 2 , deep, confusion-limited maps at three different bands, centered on the Great Observatories Origins Deep Survey South Field. By calculating the covariance of these maps with catalogs of 24 μm sources from the Far-Infrared Deep Extragalactic Legacy Survey, we have determined that the total submillimeter intensities are 8.60 ± 0.59, 4.93 ± 0.34, and 2.27 ± 0.20 nW m −2 sr −1 at 250, 350, and 500 μm, respectively. These numbers are more precise than previous estimates of the cosmic infrared background (CIB) and are consistent with 24 μm-selected galaxies generating the full intensity of the CIB. We find that the fraction of the CIB that originates from sources at z ⩾ 1.2 increases with wavelength, with 60% from high-redshift sources at 500 μm. At all BLAST wavelengths, the relative intensity of high- z sources is higher for 24 μm-faint sources than that for 24 μm-bright sources. Galaxies identified as active galactic nuclei (AGNs) by their Infrared Array Camera colors are 1.6–2.6 times brighter than the average population at 250–500 μm, consistent with what is found for X-ray-selected AGNs. BzK -selected galaxies are found to be moderately brighter than typical 24 μm-selected galaxies in the BLAST bands. These data provide high-precision constraints for models of the evolution of the number density and intensity of star-forming galaxies at high redshift.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.052 | 0.019 |
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".