The R-Process Alliance: Abundance Universality among Some Elements at and between the First and Second R-Process Peaks*
Bibliographic record
Abstract
Abstract We present new observational benchmarks of rapid neutron-capture process (r-process) nucleosynthesis for elements at and between the first (A ∼ 80) and second (A ∼ 130) peaks. Our analysis is based on archival ultraviolet and optical spectroscopy of eight metal-poor stars with Se (Z = 34) or Te (Z = 52) detections, whose r-process enhancement varies by more than a factor of 30 (−0.22 ≤ [Eu/Fe] ≤ +1.32). We calculate ratios among the abundances of Se, Sr through Mo (38 ≤ Z ≤ 42), and Te. These benchmarks may offer a new empirical alternative to the predicted solar system r-process residual pattern. The Te abundances in these stars correlate more closely with the lighter r-process elements than the heavier ones, contradicting and superseding previous findings. The small star-to-star dispersion among the abundances of Se, Sr, Y, Zr, Nb, Mo, and Te (≤0.13 dex, or 26%) matches that observed among the abundances of the lanthanides and third r-process-peak elements. The concept of r-process universality that is recognized among the lanthanide and third-peak elements in r-process-enhanced stars may also apply to Se, Sr, Y, Zr, Nb, Mo, and Te, provided the overall abundances of the lighter r-process elements are scaled independently of the heavier ones. The abundance behavior of the elements Ru through Sn (44 ≤ Z ≤ 50) requires further study. Our results suggest that at least one relatively common source in the early Universe produced a consistent abundance pattern among some elements spanning the first and second r-process peaks.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".