The AGN fraction of submm-selected galaxies and contributions to the submm/mm-wave extragalactic background light
Bibliographic record
Abstract
We present a comparison of the SCUBA half degree extragalactic survey (SHADES) at 450 μm, 850 μm and 1100 μm with deep guaranteed time 15 μm AKARI FU-HYU survey data and Spitzer guaranteed time data at 3.6-24 μm in the Lockman hole east. The AKARI data was analysed using bespoke software based in part on the drizzling and minimum-variance matched filtering developed for SHADES, and was cross-calibrated against ISO fluxes. Our stacking analyses find AKARI 15 μm galaxies with $\ga$200 μJy contribute >10% of the 450 μm background, but only <4% of the 1100 μm background, suggesting that different populations contribute at mm-wavelengths. We confirm our earlier result that the ultra-deep 450 μm SCUBA-2 cosmology survey will be dominated by populations already detected by AKARI and Spitzer mid-infrared surveys. The superb mid-infrared wavelength coverage afforded by combining Spitzer and AKARI photometry is an excellent diagnostic of AGN contributions, and we find that (23-52)% of submm-selected galaxies have AGN bolometric fractions fAGN > 0.3.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".