MeerKAT HI commissioning observations of MHONGOOSE galaxy ESO 302-G014
Bibliographic record
Abstract
Aims. We present the results of three commissioning H I observations obtained with the MeerKAT radio telescope. These observations make up part of the preparation for the forthcoming MHONGOOSE nearby galaxy survey, which is a MeerKAT large survey project that will study the accretion of gas in galaxies and the link between gas and star formation. Methods. We used the available H I data sets, along with ancillary data at other wavelengths, to study the morphology of the MHONGOOSE sample galaxy, ESO 302-G014, which is a nearby gas-rich dwarf galaxy. Results. We find that ESO 302-G014 has a lopsided, asymmetric outer disc with a low column density. In addition, we find a tail or filament of H I clouds extending away from the galaxy, as well as an isolated H I cloud some 20 kpc to the south of the galaxy. We suggest that these features indicate a minor interaction with a low-mass galaxy. Optical imaging shows a possible dwarf galaxy near the tail, but based on the current data, we cannot confirm any association with ESO 302-G014. Nonetheless, an interaction scenario with some kind of low-mass companion is still supported by the presence of a significant amount of molecular gas, which is almost equal to the stellar mass, and a number of prominent stellar clusters, which suggest recently triggered star formation. Conclusions. These data show that MeerKAT produces exquisite imaging data. The forthcoming full-depth survey observations of ESO 302-G014 and other sample galaxies will, therefore, offer insights into the fate of neutral gas as it moves from the intergalactic medium onto 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 | 0.001 | 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".