Linking the dust and chemical evolution: Taurus and Perseus
Bibliographic record
Abstract
Context. HCN, HNC, and their isotopologues are ubiquitous molecules that can serve as chemical thermometers and evolutionary tracers to characterize star-forming regions. Despite their importance in carrying information that is vital to studies of the chemistry and evolution of star-forming regions, the collision rates of some of these molecules have not been available for rigorous studies in the past. Aims. Our goal is to perform an up-to-date gas and dust chemical characterization of two different star-forming regions, TMC 1-C and NGC 1333-C7, using new collisional rates of HCN, HNC, and their isotopologues. We investigated the possible effects of the environment and stellar feedback in their chemistry and their evolution. Methods. We used updated collisional rates of HCN, HNC, and their isotopologues in our analysis of the chemistry of TMC 1-C (Taurus) and NGC 1333-C7 (Perseus). With millimeter observations, we derived their column densities, the C and N isotopic fractions, the isomeric ratios, and the deuterium fractionation. The continuum data at 3 mm and 850 µm allowed us to compute the emissivity spectral index and look for grain growth as an evolutionary tracer. Results. The H13CN/HN13C ratio is anticorrelated with the deuterium fraction of HCN, thus it can readily serve as a proxy for the temperature. The spectral index (β ~ 1.34–2.09) shows a tentative anticorrelation with the H13CN/HN13C ratio, suggesting grain growth in the evolved, hotter, and less deuterated sources. Unlike TMC 1-C, the south-to-north gradient in dust temperature and spectral index observed in NGC 1333-C7 suggests feedback from the main NGC 1333 cloud. Conclusions. With this up-to-date characterization of two star-forming regions, we found that the chemistry and the physical properties are tightly related. The dust temperature, deuterium fraction, and the spectral index are complementary evolutionary tracers. The large-scale environmental factors may dominate the chemistry and evolution in clustered star-forming regions.
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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".