IROCKS: SPATIALLY RESOLVED KINEMATICS OF z ∼ 1 STAR-FORMING GALAXIES
Bibliographic record
Abstract
ABSTRACT We present results from the Intermediate Redshift OSIRIS Chemo-Kinematic Survey (IROCKS) for sixteen z ∼ 1 and one z ∼ 1.4 star-forming galaxies. All galaxies were observed with OSIRIS with the laser guide star adaptive optics system at Keck Observatory. We use rest-frame nebular Hα emission lines to trace morphologies and kinematics of ionized gas in star-forming galaxies on sub-kiloparsec physical scales. We observe elevated velocity dispersions (σ ≳ 50 km s−1) seen in z > 1.5 galaxies persist at z ∼ 1 in the integrated galaxies. Using an inclined disk model and the ratio of , we find that 1/3 of the z ∼ 1 sample are disk candidates while the other 2/3 of the sample are dominated by merger-like and irregular sources. We find that including extra attenuation toward H ii regions derived from stellar population synthesis modeling brings star formation rates (SFRs) using Hα and stellar population fit into a better agreement. We explore the properties of the compact Hα sub-component, or “clump,” at z ∼ 1 and find that they follow a similar size–luminosity relation as local H ii regions but are scaled-up by an order of magnitude with higher luminosities and sizes. Comparing the z ∼ 1 clumps to other high-redshift clump studies, we determine that the clump SFR surface density evolves as a function of redshift. This suggests clump formation is directly related to the gas fraction in these systems and may support disk fragmentation as their formation mechanism since gas fraction scales with redshift.
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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 | 0.000 | 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".