Near-infrared Spectroscopy of Five Ultra-massive Galaxies at 1.7 < z < 2.7
Bibliographic record
Abstract
We present the results of a pilot near-infrared spectroscopic campaign of five very massive galaxies () in the range of . We measure an absorption feature redshift for one galaxy at . For the remaining galaxies, we combine the photometry with the continuum from the spectra to estimate continuum redshifts and stellar population properties. We define a continuum redshift ( ) as one in which the redshift is estimated probabilistically from the combination of catalog photometry and the observed spectrum using EAZY. We derive the uncertainties on the stellar population synthesis properties using a Monte Carlo simulation and examine the correlations between the parameters with and without the use of the spectrum in the modeling of the spectral energy distributions. The spectroscopic constraints confirm the extreme stellar masses of the galaxies in our sample. We find that three out of five galaxies are quiescent (star-formation rate of ) with low levels of dust obscuration () , that one galaxy displays both high levels of star formation and dust obscuration (, mag), and that the remaining galaxy has properties that are intermediate between the quiescent and star-forming populations.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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 | 0.000 |
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".