The HASHTAG project I. A survey of CO(3–2) emission from the star forming disc of M31
Bibliographic record
Abstract
ABSTRACT We present a CO(3–2) survey of selected regions in the M31 disc as part of the JCMT large programme, HARP and SCUBA-2 High-Resolution Terahertz Andromeda Galaxy Survey (HASHTAG). The 12 CO(3–2) fields in this survey cover a total area of 60 arcmin2, spanning a deprojected radial range of 2–14 kpc across the M31 disc. Combining these observations with existing IRAM 30 m CO(1–0) observations and JCMT CO(3–2) maps of the nuclear region of M31, as well as dust temperature and star formation rate surface density maps, we are able to explore the radial distribution of the CO(3–2)/CO(1–0) integrated intensity ratio (R31) and its relationship with dust temperature and star formation. We find that the value of R31 between 2 and 9 kpc galactocentric radius is 0.14, significantly lower than what is seen in the nuclear ring at 1 kpc (R31 ∼ 0.8), only to rise again to 0.27 for the fields centred on the 10 kpc star forming ring. We also found that R31 is positively correlated with dust temperature, with Spearman’s rank correlation coefficient ρ = 0.55. The correlation between star formation rate surface density and CO(3–2) intensity is much stronger than with CO(1–0), with ρ = 0.54 compared to –0.05, suggesting that the CO(3–2) line traces warmer and denser star forming gas better. We also find that R31 correlates well with star formation rate surface density, with ρ = 0.69.
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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 | 0.001 |
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".