GASKAP-HI Pilot Survey Science III: An unbiased view of cold gas in the Small Magellanic Cloud
Bibliographic record
Abstract
Abstract We present the first unbiased survey of neutral hydrogen absorption in the Small Magellanic Cloud. The survey utilises pilot neutral hydrogen observations with the Australian Square Kilometre Array Pathfinder telescope as part of the Galactic Australian Square Kilometre Array Pathfinder neutral hydrogen project whose dataset has been processed with the Galactic Australian Square Kilometre Array Pathfinder-HI absorption pipeline, also described here. This dataset provides absorption spectra towards 229 continuum sources, a 275% increase in the number of continuum sources previously published in the Small Magellanic Cloud region, as well as an improvement in the quality of absorption spectra over previous surveys of the Small Magellanic Cloud. Our unbiased view, combined with the closely matched beam size between emission and absorption, reveals a lower cold gas faction (11%) than the 2019 ATCA survey of the Small Magellanic Cloud and is more representative of the Small Magellanic Cloud as a whole. We also find that the optical depth varies greatly between the Small Magellanic Cloud’s bar and wing regions. In the bar we find that the optical depth is generally low (correction factor to the optically thin column density assumption of $\mathcal{R}_{\mathrm{HI}} \sim 1.04$ ) but increases linearly with column density. In the wing however, there is a wide scatter in optical depth despite a tighter range of column densities.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".