Dust-obscured star formation in the outskirts of XMMU J2235.3−2557, a massive galaxy cluster at z = 1.4★
Bibliographic record
Abstract
Star formation (SF) in the galaxy populations of local massive clusters is reduced with respect to field galaxies, and tends to be suppressed in the core region. Indications of a reversal of the SF–density relation have been observed in a few z > 1.4 clusters. Using deep imaging from 100–500 μm from Photodetector Array Camera and Spectrometer (PACS) and Spectral and Photometric Imaging REceiver (SPIRE) onboard Herschel, we investigate infrared properties of spectroscopic and photo-z cluster members, and of Hα emitters in XMMU J2235.3−2557, one of the most massive, distant, X-ray selected clusters known. Our analysis is based mostly on fitting of the galaxies spectral energy distribution (SED) in the rest-frame 8–1000 μm. We measure total IR luminosity, deriving star formation rates (SFRs) ranging from 89 to 463 M⊙ yr−1 for 13 galaxies individually detected by Herschel, all located beyond the core region (r >250 kpc). We perform a stacking analysis of nine star-forming members not detected by PACS, yielding a detection with SFR = 48 ± 16 M⊙ yr−1. Using a colour criterion based on a star-forming galaxy SED at the cluster redshift, we select 41 PACS sources as candidate star-forming cluster members. We characterize a population of highly obscured SF galaxies in the outskirts of XMMU J2235.3−2557. We do not find evidence for a reversal of the SF–density relation in this massive, distant cluster.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 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".