A SCUBA/Spitzer investigation of the far-infrared extragalactic background
Bibliographic record
Abstract
We have measured the contribution of submillimetre and mid-infrared sources to the extragalactic background radiation at 70 and 160 μm. Specifically, we have stacked flux in 70- and 160-μm Spitzer Space Telescope (Spitzer) observations of the Canada–United Kingdom Deep Submillimetre Survey 14-h field at the positions of 850-μm sources detected by SCUBA and also 8- and 24-μm sources detected by Spitzer. We find that per source, the SCUBA galaxies are the strongest and the 8-μm sources the weakest contributors to the background flux at both 70 and 160 μm. Our estimate of the contribution of the SCUBA sources is higher than previous estimates. However, expressed as a total contribution, the full 8-μm source catalogue accounts for twice the total 24-μm source contribution and ∼10 times the total SCUBA source contribution. The 8-μm sources account for the majority of the background radiation at 160 μm with a flux of 0.87 ± 0.16 MJy sr−1 and at least a third at 70 μm with a flux of 0.103 ± 0.019 MJy sr−1. These measurements are consistent with current lower limits on the background at 70 and 160 μm. Finally, we have investigated the 70- and 160-μm emission from the 8- and 24-μm sources as a function of redshift. We find that the average 70-μm flux per 24-μm source and the average 160-μm flux per 8- and 24-μm source is constant over all redshifts, up to z∼ 4. In contrast, the low-redshift half (z < 1) of the of 8-μm sample contributes approximately four times the total 70-μm flux of the high-redshift half. These trends can be explained by a single non-evolving SED.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| 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) | 0.001 | 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".