Pop III <i>i</i>-process nucleosynthesis and the elemental abundances of SMSS J0313−6708 and the most iron-poor stars
Bibliographic record
Abstract
Abstract We have investigated a highly energetic H-ingestion event during shell He burning leading to H-burning luminosities of log (LH/L⊙) ∼ 13 in a 45 M⊙ Pop III massive stellar model. In order to track the nucleosynthesis which may occur in such an event, we run a series of single-zone nucleosynthesis models for typical conditions found in the stellar evolution model. Such nucleosynthesis conditions may lead to i-process neutron densities of up to ∼1013 cm−3. The resulting simulation abundance pattern, where Mg comes from He burning and Ca from the i process, agrees with the general observed pattern of the most iron-poor star currently known, SMSS J031300.36−670839.3. However, Na is also efficiently produced in these i-process conditions, and the prediction exceeds observations by ∼2.5 dex. While this probably rules out this model for SMSS J031300.36−670839.3, the typical i-process signature of combined He burning and i process of higher than solar [Na/Mg], [Mg/Al], and low [Ca/Mg] is reproducing abundance features of the two next most iron-poor stars HE 1017−5240 and HE 1327−2326 very well. The i process does not reach Fe which would have to come from a low level of additional enrichment. i process in hyper-metal-poor or Pop III massive stars may be able to explain certain abundance patterns observed in some of the most metal-poor CEMP-no stars.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".