High-redshift elliptical galaxies: are they (all) really compact?
Bibliographic record
Abstract
We investigate the properties of 12 ultramassive passively evolving early-type galaxies (ETGs) at zphot > 1.4 in the COSMOS 2 deg2 field. These 12 ETGs were selected as pBzKs, have accurate 1.4 ≲zphot≲ 1.7, high Sérsic index profiles typical of ellipticals, no detection at 24 μm, resulting in a complete ETG sample at M* > 2.5 × 1011 M⊙ (Chabrier initial mass function). Contrary to the previous claims, the half-light radii estimated in very high signal-to-noise ratio imaging data from Hubble Space Telescope+Advanced Camera for Surveys (ACS) are found to be large for most of the sample, consistent with local ellipticals. If the high-redshift ETGs with M* < 2.5 × 1011 M⊙ are really small in size and compact as reported in the previous studies, our result may suggest a ‘downsizing’ scenario, whereby the most massive ETGs reach their final structure earlier and faster than the lower mass ones. However, simulating galaxies with morphological properties fixed to those of local ETGs with the same stellar mass show that the few compact galaxies that we still recover in our sample can be understood in terms of fluctuations due to noise preventing the recovery of the extended low surface brightness haloes in the light profile. Such haloes, typical of Sérsic profiles, extending even up to 40 kpc, are indeed seen in our sample.
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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 | 0.001 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".