The Properties of the Star-Forming Interstellar Medium at z=0.84-2.23\n from HiZELS - I: Mapping the Internal Dynamics and Metallicity Gradients in\n High-Redshift Disk Galaxies
Bibliographic record
Abstract
We present adaptive optics assisted, spatially resolved spectroscopy of a\nsample of nine H-alpha-selected galaxies at z=0.84--2.23 drawn from the HiZELS\nnarrow-band survey. These galaxies have star-formation rates of 1-27Mo/yr and\nare therefore representative of the typical high-redshift star-forming\npopulation. Our ~kpc-scale resolution observations show that approximately half\nof the sample have dynamics suggesting that the ionised gas is in large,\nrotating disks. We model their velocity fields to infer the\ninclination-corrected, asymptotic rotational velocities. We use the absolute\nB-band magnitudes and stellar masses to investigate the evolution of the B-band\nand stellar mass Tully-Fisher relationships. By combining our sample with a\nnumber of similar measurements from the literature, we show that, at fixed\ncircular velocity, the stellar mass of star-forming galaxies has increased by a\nfactor 2.5 between z=2 and z=0, whilst the rest-frame B-band luminosity has\ndecreased by a factor ~6 over the same period. Together, these demonstrate a\nchange in mass-to-light ratio in the B-band of Delta(M/L_B)/(M/L_B)_(z=0) \\sim\n3.5 between z=1.5 and z=0, with most of the evolution occurring below z=1. We\nalso use the spatial variation of [NII]/Halpha to show that the metallicity of\nthe ionised gas in these galaxies declines monotonically with galacto-centric\nradius, with an average Delta(log O/H)/DeltaR=-0.027+/-0.005dex/kpc. This\ngradient is consistent with predictions for high-redshift disk galaxies from\ncosmologically based hydrodynamic simulations.\n
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".