THE<sup>12</sup>C +<sup>12</sup>C REACTION AND THE IMPACT ON NUCLEOSYNTHESIS IN MASSIVE STARS
Bibliographic record
Abstract
Despite much effort in the past decades, the C-burning reaction rate is uncertain by several orders of magnitude, and the relative strength between the different channels 12 C( 12 C, α) 20 Ne, 12 C( 12 C, p ) 23 Na, and 12 C( 12 C, n ) 23 Mg is poorly determined. Additionally, in C-burning conditions a high 12 C+ 12 C rate may lead to lower central C-burning temperatures and to 13 C(α, n ) 16 O emerging as a more dominant neutron source than 22 Ne(α, n ) 25 Mg, increasing significantly the s -process production. This is due to the chain 12 C( p , γ) 13 N followed by 13 N(β +) 13 C, where the photodisintegration reverse channel 13 N(γ, p ) 12 C is strongly decreasing with increasing temperature. Presented here is the impact of the 12 C+ 12 C reaction uncertainties on the s -process and on explosive p -process nucleosynthesis in massive stars, including also fast rotating massive stars at low metallicity. Using various 12 C+ 12 C rates, in particular an upper and lower rate limit of ∼50,000 higher and ∼20 lower than the standard rate at 5 × 10 8 K, five 25 M ☉ stellar models are calculated. The enhanced s -process signature due to 13 C(α, n ) 16 O activation is considered, taking into account the impact of the uncertainty of all three C-burning reaction branches. Consequently, we show that the p -process abundances have an average production factor increased up to about a factor of eight compared with the standard case, efficiently producing the elusive Mo and Ru proton-rich isotopes. We also show that an s -process being driven by 13 C(α, n ) 16 O is a secondary process, even though the abundance of 13 C does not depend on the initial metal content. Finally, implications for the Sr-peak elements inventory in the solar system and at low metallicity are discussed.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".