MHONGOOSE: A MeerKAT nearby galaxy H I survey
Why this work is in the frame
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Bibliographic record
Abstract
The MHONGOOSE (MeerKAT H I Observations of Nearby Galactic Objects: Observing Southern Emitters) survey maps the distribution and kinematics of the neutral atomic hydrogen (H I ) gas in and around 30 nearby star-forming spiral and dwarf galaxies to extremely low H I column densities. The H I column density sensitivity (3 σ over 16 km s −1 ) ranges from ∼5 × 10 17 cm −2 at 90″ resolution to ∼4 × 10 19 cm −2 at the highest resolution of 7″. The H I mass sensitivity (3 σ over 50 km s −1 ) is ∼5.5 × 10 5 M ⊙ at a distance of 10 Mpc (the median distance of the sample galaxies). The velocity resolution of the data is 1.4 km s −1 . One of the main science goals of the survey is the detection of cold accreting gas in the outskirts of the sample galaxies. The sample was selected to cover a range in H I masses from 10 7 M ⊙ to almost 10 11 M ⊙ in order to optimally sample possible accretion scenarios and environments. The distance to the sample galaxies ranges from 3 to 23 Mpc. In this paper, we present the sample selection, survey design, and observation and reduction procedures. We compared the integrated H I fluxes based on the MeerKAT data with those derived from single-dish measurement and find good agreement, indicating that our MeerKAT observations are recovering all flux. We present H I moment maps of the entire sample based on the first ten percent of the survey data, and find that a comparison of the zeroth- and second-moment values shows a clear separation in the physical properties of the H I between areas with star formation and areas without related to the formation of a cold neutral medium. Finally, we give an overview of the H I -detected companion and satellite galaxies in the 30 fields, five of which have not previously been cataloged. We find a clear relation between the number of companion galaxies and the mass of the main target galaxy.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 it