Constraints on pre-main-sequence evolution from stellar pulsations
Bibliographic record
Abstract
Abstract Pulsating pre-main-sequence (PMS) stars afford the earliest opportunity in the lifetime of a star to which the concepts of asteroseismology can be applied. PMS stars should be structurally simpler than their evolved counterparts, thus (hopefully!) making any asteroseismic analysis relatively easier. Unfortunately, this isn't necessarily the case. The majority of these stars (around 80) are δ Scuti pulsators, with a couple of γ Doradus, γ Doradus – δ Scuti hybrids, and slowly pulsating B stars thrown into the mix. The majority of these stars have only been discovered within the last ten years, with the community still uncovering the richness of phenomena associated with these stars, many of which defy traditional asteroseismic analysis. A systematic asteroseismic analysis of all of the δ Scuti PMS stars was performed in order to get a better handle on the properties of these stars as a group. Some strange results have been found, including one star pulsating up to the theoretical acoustic cut-off frequency of the star, and a number of stars in which the most basic asteroseismic analysis suggests problems with the stars' positions in the Hertzsprung-Russell diagram. From this we get an idea of the\break constraints — or lack thereof — that these results can put on PMS stellar evolution.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".