CEERS Spectroscopic Confirmation of NIRCam-selected z ≳ 8 Galaxy Candidates with JWST/NIRSpec: Initial Characterization of Their Properties
Bibliographic record
Abstract
Abstract We present JWST NIRSpec spectroscopy for 11 galaxy candidates with photometric redshifts of z ≃ 9 − 13 and M UV ∈ [ −21, −18] newly identified in NIRCam images in the Cosmic Evolution Early Release Science Survey. We confirm emission line redshifts for 7 galaxies at z = 7.762–8.998 using spectra at ∼1–5 μ m either with the NIRSpec prism or its three medium-resolution ( R ∼ 1000) gratings. For z ≃ 9 photometric candidates, we achieve a high confirmation rate of ≃90%, which validates the classical dropout selection from NIRCam photometry. No robust emission lines are identified in three galaxy candidates at z > 10, where the strong [O iii ] and H β lines would be redshifted beyond the wavelength range observed by NIRSpec, and the Ly α continuum break is not detected with the sensitivity of the current data. Compared with Hubble Space Telescope-selected bright galaxies ( M UV ≃ −22) that are similarly spectroscopically confirmed at z ≃ 8 − 9, these NIRCam-selected galaxies are characterized by lower star formation rates (SFRs; SFR ≃ 4 M ⊙ yr −1 ) and lower stellar masses (≃10 8 M ⊙ ), but with higher specific SFR (≃40 Gyr −1 ), higher [O iii ]+H β equivalent widths (≃1100 Å), and elevated production efficiency of ionizing photons ( log ( ξ ion / Hz erg − 1 ) ≃ 25.8 ) induced by young stellar populations (<10 Myr) accounting for ≃20% of the galaxy mass, highlighting the key contribution of faint galaxies to cosmic reionization. Taking advantage of the homogeneous selection and sensitivity, we also investigate metallicity and ISM conditions with empirical calibrations using the [O iii ] 5008 /H β ratio. We find that galaxies at z ≃ 8 − 9 have higher SFRs and lower metallicities than galaxies at similar stellar masses at z ≃ 2 − 6, which is generally consistent with the current galaxy formation and evolution models.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 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".