Calcium Excess in Novae: Beyond Nuclear Physics Uncertainties
Bibliographic record
Abstract
Abstract We examine Ca abundances in classical novae from spectroscopic observations spanning 65 yr and investigate whether they are systematically high compared to those predicted by nova models. For the first time, we perform Monte Carlo simulations assessing the impact of nuclear reaction rate uncertainties on abundances predicted by multizone nova models. While the Ca abundances in the models are sensitive to variations of rates of the reactions 37 Ar( p , γ ) 38 K and 38 K( p , γ ) 39 Ca, the nuclear physics uncertainties of these reactions cannot account for the discrepancy between the observed and predicted Ca abundances in novae. Furthermore, the overabundance of Ca has important implications for measuring 7 Be in nova ejecta, as Ca lines are used to estimate 7 Be abundances. If the Ca abundance is incorrectly determined, it could lead to inaccurate 7 Be abundance estimates. Possible alternative explanations for the observed Ca overabundance 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".