Observed CN and HCN intensity ratios exhibit subtle variations in extreme galaxy environments
Bibliographic record
Abstract
ABSTRACT We use both new and archival ALMA data of three energy lines each of CN and HCN to explore intensity ratios in dense gas in NGC 3256, NGC 7469, and IRAS 13120-5453. The HCN (3–2)/HCN (1–0) intensity ratio varies in NGC 3256 and NGC 7469, with superlinear trends of 1.53 ± 0.07 and 1.55 ± 0.05, respectively. We find an offset to higher HCN (3–2)/HCN (1–0) intensity ratios (∼0.8) in IRAS 13120-5453 compared to NGC 3256 (∼0.3−0.4) and NGC 7469 (∼0.3−0.5). The HCN (4–3)/HCN (3–2) intensity ratio in NGC 7469 has a slope of 1.34 ± 0.05. We attribute the variation within NGC 3256 to excitation associated with the northern and southern nuclei. In NGC 7469, the variations are localized to the region surrounding the active galactic nucleus. At our resolution (∼700 pc), IRAS 13120-5453 shows little variation in the HCN intensity ratios. Individual galaxies show nearly constant CN (2–1)/CN (1–0) intensity ratios. We find an offset to lower CN (2–1)/CN (1–0) intensity ratios (∼0.5) in NGC 3256 compared to the other two galaxies (∼0.8). For the CN (3–2)/CN (2–1) intensity ratio, NGC 7469 has a superlinear trend of 1.55 ± 0.04, with the peak localized towards the active galactic nucleus. We find high (∼1.7) CN (1–0)/HCN (1–0) intensity ratios in IRAS 13120-5453 and in the northern nucleus of NGC 3256, compared to a more constant ratio (∼1.1) in NGC 7469 and non-starbursting regions of NGC 3256.
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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".