Optical Spectroscopy of K-selected Extremely Red Galaxies
Bibliographic record
Abstract
We have obtained spectroscopic redshifts for 24 red galaxies from a sample with median Ks=18.7 and F814W - Ks > 4, using the Keck telescope. These EROshave high resolution morphologies from HST (Yan & Thompson 2003). Among the 24 redshifts, the majority (92%) are at $ 0.9 < z < 1.5$. We derived the rest-frame J-band luminosity function at $z_{median} =1.14$. Our result suggests that the luminosity evolution between bright EROs at $z\sim 1$ and the present-day $>$L$^*$ massive galaxies is at most about 0.7 magnitude. Combining the morphologies and deep spectroscopy revealed the following properties: (1) 86% of the spectra have absorption features from old stars, suggesting that the dominant stellar populations seen in the rest-frame UV are old stars. 50% of the sources have pure absorption lines, while the remaining 50% have emission lines, indicating recent star formation. We conclude that the color criterion for EROs is very effective in selecting old stellar populations at $z \sim 1$, and a large fraction of these systems with prominent old stellar populations also have recent star formation. (2) The 12 emission line systems have the same number of disk and bulge galaxies as in the remaining 12 pure absorption line systems. We conclude that spectral classes do not have a simple, direct correspondence with morphological types. (3) Three EROs could be isolated, pure passively evolving early-type galaxies at $z\sim 1$. This implies that only a small fraction (10%--15%) of early-type galaxies are formed in a rapid burst of star formation at high redshifts and evolved passively since then. (Abridged).
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".