A kpc-scale-resolved study of unobscured and obscured star formation activity in normal galaxies at z = 1.5 and 2.2 from ALMA and HiZELS
Bibliographic record
Abstract
ABSTRACT We present Atacama Large Millimeter/Submillimeter Array (ALMA) continuum observations of a sample of nine star-forming galaxies at redshifts 1.47 and 2.23 selected from the High-z Emission Line Survey (HiZELS). Four galaxies in our sample are detected at high significance by ALMA at a resolution of 0${_{.}^{\prime\prime}}$25 at rest-frame 355 μm. Together with the previously observed H α emission, from adaptive optics-assisted integral-field-unit spectroscopy (∼0${_{.}^{\prime\prime}}$15 resolution), and F606W and F140W imaging from the Hubble Space Telescope (∼0${_{.}^{\prime\prime}}$2 resolution), we study the star formation activity, stellar and dust mass in these high-redshift galaxies at ∼kpc-scale resolution. We find that ALMA detection rates are higher for more massive galaxies (M* > 1010.5 M⊙) and higher [N ii]/H α ratios (>0.25, a proxy for gas-phase metallicity). The dust extends out to a radius of 8 kpc, with a smooth structure, even for those galaxies presenting clumpy H α morphologies. The half-light radii (Rdust) derived for the detected galaxies are of the order ∼4.5 kpc, more than twice the size of submillimetre-selected galaxies at a similar redshift. Our global star formation rate estimates – from far-infrared and extinction-corrected H α luminosities – are in good agreement. However, the different morphologies of the different phases of the interstellar medium suggest complex extinction properties of the high-redshift normal galaxies.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".