Testing Rotational Mixing Predictions with New Boron Abundances in Main‐Sequence B‐Type Stars
Bibliographic record
Abstract
New boron abundances for seven main-sequence B-type stars are determined from HST STIS spectroscopy around the B III 2066 Å line. Boron abundances provide a unique and critical test of stellar evolution models that include rotational mixing, since boron is destroyed in the surface layers of stars through shallow mixing long before other elements are mixed from the stellar interior through deep mixing. The stars in this study are all on or near the main sequence and are members of young Galactic clusters. They show no evidence of mixing with gas from H-burning layers from their CNO abundances. Boron abundances range from 12 + log(B/H) ≤ 1.0 to 2.2. The boron abundances are compared to the published values of the stellar nitrogen abundances [all have 12 + log(N/H) ≤ 7.8] and to their host cluster ages (4-16 Myr) to investigate the predictions from models of massive star evolution with rotational mixing effects. We find that the variations in boron and nitrogen are generally within the range of the predictions from the stellar evolution models with rotation (where predictions for models with rotation rates from 0 to 450 km s -1 and μ-barriers are examined), especially given their age and mass ranges. Three stars (of 34 B-type stars with detailed boron abundance determinations) deviate from the model predictions, showing either much larger boron depletions than can be explained by the rotating model predictions or a spectroscopic mass that is lower than expected, given the rotating model predictions for its age and abundances. The results from these three stars suggest that rotational mixing could be more efficient than that currently modeled at the highest rotation rates.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.005 | 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".