<i>JWST</i> catches the assembly of a <i>z</i> ∼ 5 ultra-low-mass galaxy
Bibliographic record
Abstract
ABSTRACT Using CANUCS imaging we found an apparent major merger of two $z$ ∼ 5 ultra-low-mass galaxies (M⋆∼107M⊙ each) that are doubly imaged and magnified ∼12–15× by the lensing cluster MACS 0417. Both galaxies are experiencing young (∼100 Myr), synchronised bursts of star formation with log (sSFR/Gyr−1) ∼1.3–1.4, yet SFRs of just ∼0.2M⊙ yr−1. They have sub-solar (Z ∼ 0.2Z⊙) gas-phase metallicities and are connected by an even more metal-poor star-forming bridge. The galaxy that forms from the merger will have a mass of at least M⋆∼2 × 107 M⊙, at least half of it formed during the interaction-induced starburst. More than half of the ionizing photons produced by the system (before and during the merger) will have been produced during the burst. This system provides the first detailed look at a merger involving two high-$z$ ultra-low-mass galaxies of the type believed to be responsible for reionizing the Universe. It suggests that such galaxies can grow via a combination of mass obtained through major mergers, merger-triggered starbursts, and long-term in-situ star formation. If such high-$z$ mergers are common, then merger-triggered starbursts could be significant contributors to the ionizing photon budget of the Universe.
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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 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.004 | 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".