<i>JWST</i> UNCOVER: discovery of <i>z</i> &gt; 9 galaxy candidates behind the lensing cluster Abell 2744
Bibliographic record
Abstract
ABSTRACT We present the results of a search for high-redshift (z > 9) galaxy candidates in the JWST UNCOVER survey, using deep NIRCam and NIRISS imaging in seven bands over ∼45 arcmin2 and ancillary Hubble Space Telescope (HST) observations. The NIRCam observations reach a 5σ limiting magnitude of ∼29.2 AB. The identification of high-z candidates relies on a combination of a dropout selection and photometric redshifts. We find 16 candidates at 9 < z < 12 and three candidates at 12 < z < 13, eight candidates are deemed very robust. Their lensing amplification ranges from μ = 1.2 to 11.5. Candidates have a wide range of (lensing corrected) luminosities and young ages, with low stellar masses [6.8 < log(M⋆/M⊙) < 9.5] and low star formation rates (SFR = 0.2–7 M⊙ yr−1), confirming previous findings in early JWST observations of z > 9. A few galaxies at z ∼ 9−10 appear to show a clear Balmer break between the F356W and F444W/F410M bands, which helps constrain their stellar mass. We estimate blue UV continuum slopes between β = −1.8 and −2.3, typical for early galaxies at z > 9 but not as extreme as the bluest recently discovered sources. We also find evidence for a rapid redshift-evolution of the mass-luminosity relation and a redshift evolution of the UV continuum slope for a given range of intrinsic magnitude, in line with theoretical predictions. These findings suggest that deeper JWST observations are needed to reach the fainter galaxy population at those early epochs, and follow-up spectroscopy will help better constrain the physical properties and star formation histories of a larger sample of galaxies.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".