The MALATANG survey: dense gas and star formation from high-transition HCN and HCO+ maps of NGC 253
Bibliographic record
Abstract
ABSTRACT To study the high-transition dense-gas tracers and their relationships to the star formation of the inner ∼2 kpc circumnuclear region of NGC 253, we present HCN J = 4−3 and HCO+ J = 4−3 maps obtained with the James Clerk Maxwell Telescope. Using the spatially resolved data, we compute the concentration indices r90/r50 for the different tracers. HCN and HCO+ 4–3 emission features tend to be centrally concentrated, which is in contrast to the shallower distribution of CO 1–0 and the stellar component. The dense-gas fraction (fdense, traced by the velocity-integrated-intensity ratios of HCN/CO and HCO+/CO) and the ratio R31 (CO 3–2/1–0) decline towards larger galactocentric distances, but increase with higher star formation rate surface density. The radial variation and the large scatter of fdense and R31 imply distinct physical conditions in different regions of the galactic disc. The relationships of fdense versus Σstellar, and SFEdense versus Σstellar are explored. SFEdense increases with higher Σstellar in this galaxy, which is inconsistent with previous work that used HCN 1–0 data. This implies that existing stellar components might have different effects on the high-J HCN and HCO+ than their low-J emission. We also find that SFEdense seems to be decreasing with higher fdense which is consistent with previous works, and it suggests that the ability of the dense gas to form stars diminishes when the average density of the gas increases. This is expected in a scenario where only the regions with high-density contrast collapse and form stars.
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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 | 0.000 |
| 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".