The MUSE Atlas of Discs (MAD): Ionized gas kinematic maps and an application to diffuse ionized gas
Bibliographic record
Abstract
ABSTRACT We have obtained data for 41 star forming galaxies in the MUSE Atlas of Discs (MAD) survey with VLT/MUSE. These data allow us, at high resolution of a few 100 pc, to extract ionized gas kinematics (V, σ) of the centres of nearby star forming galaxies spanning 3 dex in stellar mass. This paper outlines the methodology for measuring the ionized gas kinematics, which we will use in subsequent papers of this survey. We also show how the maps can be used to study the kinematics of diffuse ionized gas for galaxies of various inclinations and masses. Using two different methods to identify the diffuse ionized gas, we measure rotation velocities of this gas for a subsample of six galaxies. We find that the diffuse ionized gas rotates on average slower than the star forming gas with lags of 0–10 km s−1 while also having higher velocity dispersion. The magnitude of these lags is on average 5 km s−1 lower than observed velocity lags between ionized and molecular gas. Using Jeans models to interpret the lags in rotation velocity and the increase in velocity dispersion we show that most of the diffuse ionized gas kinematics are consistent with its emission originating from a somewhat thicker layer than the star forming gas, with a scale height that is lower than that of the stellar disc.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".