Seismology of Pre‐Main‐Sequence Stars in NGC 6530
Bibliographic record
Abstract
Nonradial p -mode oscillation spectra, computed from a dense grid of pre-main-sequence models, are fit to observed oscillation spectra of several stars in the young cluster NGC 6530. The five stars we consider, all previously identified as pulsating pre-main-sequence stars, each have from two to nine observed oscillation frequencies. For those stars with a more complete set of frequencies we are able to constrain the models using the oscillation spectra alone and confirm that the stars are in their pre-main-sequence and not post-main-sequence phase of evolution. For the stars with only two observed frequencies we are able to reduce the solution space of possible models. Comparing our model fits to the surface temperatures and luminosities derived from the observed colors and parallaxes, we find that the model fits are consistent with the cluster's distance, i.e., the luminosities agree, but we discover that all of our models are systematically too cool. We attribute some of the discrepancy in the surface temperature to uncertainties in the surface boundary conditions of our models, but argue that most of the difference is a direct consequence of applying a single average color-dependent dereddening correction to all the stars when, in fact, it appears that the stars we selected are embedded in varying degrees of gas and dust. For one of the stars we identify a rotationally split l = 1 p -mode from which we derive a rotation period of 18 days.
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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 | 0.000 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".