<i>Spitzer</i> Identifications and Classifications of Submillimeter Galaxies in Giant, High-Redshift, Lyα-Emission-Line Nebulae
Bibliographic record
Abstract
Using Spitzer Space Telescope IRAC (3.6-8 μm) and MIPS (24 μm) imaging, as well as Hubble Space Telescope optical observations, we identify the IRAC counterparts of the luminous power sources residing within the two largest and brightest Lyα-emitting nebulae (LABs) in the SA 22 protocluster at z = 3.09 (LAB 1 and LAB 2). These sources are also both submillimeter galaxies (SMGs). From their rest-frame optical/near-infrared colors, we conclude that the SMG in LAB 1 is likely starburst dominated and heavily obscured ( A V ~ 3). In contrast, LAB 2 has excess rest-frame ~2 μm emission (over that expected from starlight) and hosts a hard-X-ray-emitting active galactic nucleus (AGN) at the proposed location of the SMG, consistent with the presence of an AGN. We conclude that LAB 1 and LAB 2 appear to have very different energy sources despite having similar Lyα spatial extents and luminosities, although it remains unclear whether ongoing star formation or periodic AGN heating is responsible for the extended Lyα emission. We find that the mid-infrared properties of the SMGs lying in LAB 1 and LAB 2 are similar to those of the wider SMG population, and so it is possible that extended Lyα halos are a common feature of SMGs in general.
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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 | 0.004 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".