WALLABY pre-pilot survey: ultra-diffuse galaxies in the Eridanus supergroup
Bibliographic record
Abstract
ABSTRACT We present a pilot study of the atomic neutral hydrogen gas (H i) content of ultra-diffuse galaxy (UDG) candidates. In this paper, we use the pre-pilot Eridanus field data from the Widefield ASKAP L-band Legacy All-sky Blind Survey to search for H i in UDG candidates found in the Systematically Measuring Ultra-diffuse Galaxies survey (SMUDGes). We narrow down to 78 SMUDGes UDG candidates within the maximum radial extents of the Eridanus subgroups for this study. Most SMUDGes UDGs candidates in this study have effective radii smaller than 1.5 kpc and thus fail to meet the defining size threshold. We only find one H i detection, which we classify as a low-surface-brightness dwarf. Six putative UDGs are H i-free. We show the overall distribution of SMUDGes UDG candidates on the size–luminosity relation and compare them with low-mass dwarfs on the atomic gas fraction versus stellar mass scaling relation. There is no correlation between gas-richness and colour indicating that colour is not the sole parameter determining their H i content. The evolutionary paths that drive galaxy morphological changes and UDG formation channels are likely the additional factors to affect the H i content of putative UDGs. The actual numbers of UDGs for the Eridanus and NGC 1332 subgroups are consistent with the predicted abundance of UDGs and the halo virial mass relation, except for the NGC 1407 subgroup, which has a smaller number of UDGs than the predicted number. Different group environments suggest that these putative UDGs are likely formed via the satellite accretion scenario.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".