Investigating the HI distribution and kinematics of ESO444-G084 and [KKS2000]23: New insights from the MHONGOOSE survey
Bibliographic record
Abstract
We present the HI distribution, kinematics, mass modeling, and disk stability of the dwarf irregular galaxies ESO444-G084 and [KKS2000]23 using high-resolution, high-sensitivity MHONGOOSE survey data from MeerKAT. ESO444-G084 shows centrally concentrated HI emission, while [KKS2000]23 exhibits irregular high-density clumps. Total HI fluxes measured down to 10^19 and 10^18 cm^-2 are nearly identical, indicating that the increased HI diameter at lower column densities results mainly from the larger beam, with no significant extra emission detected. We derive total HI masses of (1.1 +/- 0.1) x 10^8 and (6.1 +/- 0.3) x 10^8 solar masses for ESO444-G084 and [KKS2000]23, respectively. Using PyFAT and TiRiFiC, we extract 3D rotation curves that reveal disk-like kinematics in both galaxies. ESO444-G084 shows a warp beyond ~1.8 kpc and a fast-rising curve consistent with a centrally concentrated dark matter distribution, while [KKS2000]23's more gradual rise suggests a more extended halo. Mass modeling with an isothermal halo and stellar mass-to-light ratios of 0.20 for ESO444-G084 and 0.18 for [KKS2000]23 yields consistent results. We analyze disk stability using spatially resolved Toomre Q and gas-to-critical surface density ratios, linking these with H-alpha and FUV-based star formation. ESO444-G084 supports localized star formation despite global stability, while [KKS2000]23 appears gravitationally unstable yet lacks H-alpha, suggesting that turbulence, gas depletion, or past feedback suppresses star formation. No inflows or outflows are detected, indicating internal processes regulate star formation. This study highlights the interplay between HI morphology, kinematics, dark matter distribution, and disk stability, showing how internal processes shape dwarf galaxy evolution.
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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 | 0.001 |
| 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".