A sensitivity study of the neutral-neutral reactions C + C3 and C + C5 in cold dense interstellar clouds
Bibliographic record
Abstract
Chemical networks used for models of interstellar clouds contain many reactions, some of them with poorly determined rate coefficients and/or products. In this work, we report a method for improving the predictions of molecular abundances using sensitivity methods and ab initio calculations. Based on the chemical network osu.2003, we used two different sensitivity methods to determine the most important reactions as a function of time for models of dense cold clouds. Of these reactions, we concentrated on those between C and C3 and between C and C5, both for their effect on specific important species such as CO and for their general effect on large numbers of species. We then used ab initio and kinetic methods to determine an improved rate coefficient for the former reaction and a new set of products, plus a slightly changed rate coefficient for the latter. Putting our new results in a pseudo-time-dependent model of cold dense clouds, we found that the abundances of many species are altered at early times, based on large changes in the abundances of CO and atomic C. We compared the effect of these new rate coefficients/products on the comparison with observed abundances and found that they shift the best agreement from 3e4 yr to (1-3)e5 yr.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".