Stellar Half-mass Radii of 0.5 z < 2.3 Galaxies: Comparison with JWST/NIRCam Half-light Radii
Bibliographic record
Abstract
Abstract We use CEERS JWST/NIRCam imaging to measure rest-frame near-IR light profiles of 435 M ⋆ > 1010 M ⊙ galaxies in the redshift range of 0.5 < z < 2.3. We compare the resulting rest-frame 1.5–2 μm half-light radii (R NIR) with stellar half-mass radii ( R M ⋆ ) derived with multicolor light profiles from CANDELS Hubble Space Telescope imaging. In general agreement with previous work, we find that R NIR and R M ⋆ are up to 40% smaller than the rest-frame optical half-light radius R opt. The agreement between R NIR and R M ⋆ is excellent, with a negligible systematic offset (<0.03 dex) up to z = 2 for quiescent galaxies and up to z = 1.5 for star-forming galaxies. We also deproject the profiles to estimate R M ⋆ , 3 D , the radius of a sphere containing 50% of the stellar mass. We present the R−M ⋆ distribution of galaxies at 0.5 < z < 1.5, comparing R opt, R M ⋆ , and R M ⋆ , 3 D . The slope is significantly flatter for R M ⋆ and R M
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".