Stored in the archives: Uncovering the CN/CO intensity ratio with ALMA in nearby U/LIRGs
Bibliographic record
Abstract
We present an archival Atacama Large Millimeter/submillimeter Array (ALMA) study of the CN N = 1 - 0 / CO J = 1 - 0 intensity ratio in nearby (z < 0.05) Ultra Luminous and Luminous Infrared Galaxies (U/LIRGs). We identify sixteen U/LIRGs that have been observed in both CN and CO lines at $\sim$ 500 pc resolution based on sixteen different ALMA projects. We measure the (CN bright)/CO and (CN bright)/(CN faint) intensity ratios at an ensemble of molecular clouds scales (CN bright = CN N = 1 - 0, J = 3/2 - 1/2; CN faint = CN N = 1 - 0, J = 1/2 - 1/2 hyperfine groupings). Our global measured (CN bright)/CO ratios range from 0.02-0.15 in LIRGs and 0.08-0.17 in ULIRGs. We attribute the larger spread in LIRGs to the variety of galaxy environments included in our sample. Overall, we find that the (CN bright)/CO ratio is higher in nuclear regions, where the physical and excitation conditions favour increased CN emission relative to the disk regions. 10 out of 11 galaxies which contain well-documented active galactic nuclei show higher ratios in the nucleus compared to the disk. Finally, we measure the median resolved (CN bright)/(CN faint) ratio and use it to estimate the total integrated CN line optical depth in ULIRGs ($τ\sim$ 0.96) and LIRGs ($τ\sim$ 0.23). The optical depth difference is likely due to the higher molecular gas surface densities found in the more compact ULIRG systems.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".