EPOCHS. XI. The Structure and Morphology of Galaxies in the Epoch of Reionization to <i>z</i> ∼ 12.5
Bibliographic record
Abstract
Abstract We present a structural analysis of 520 galaxy candidates at 6.5 < z < 12.5 with a signal-to-noise ratio of >10 σ in the F444W filter taken from the EPOCHS v1 sample, consisting of uniformly reduced deep JWST NIRCam data covering the CEERS, JADES GOODS-S, NGDEEP, SMACS-0723, GLASS, and PEARLS surveys. We use standard software to fit single Sérsic models to each galaxy in the rest-frame optical and extract their parametric structural parameters (Sérsic index, half-light radius, and axis ratio) and Morfometryka to measure their nonparametric concentration and asymmetry parameters. We find a wide range of sizes for these early galaxies, with galaxy sizes overall continuing to become progressively smaller in the high-redshift regime, following R e = 2.12 ± 0.28 1 + z − 0.67 ± 0.06 kpc. We further find a galaxy size–mass correlation up to z ∼ 12, with galaxies of a given mass also becoming smaller. Using nonparametric methods, we find that galaxy merger fractions, classified through asymmetry parameters, at these redshifts remain consistent with those in the literature, maintaining a value of f m ∼ 0.12 ± 0.07 showing little dependence with redshift when combined with the literature at z > 4. We find that galaxies that are smaller in size also appear rounder, with an excess of high axis ratio objects. Finally, we artificially redshift a subsample of our objects to determine how robust the observational trends we see are, determining that the observed trends are due to real evolutionary effects, rather than being a consequence of redshift effects.
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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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".