Normal A0-A1 stars with low v sin i
Bibliographic record
Abstract
Context. The study of rotational velocity distributions for normal stars requires an accurate spectral characterization of the objects in order to avoid polluting the results with undetected binary or peculiar stars. This piece of information is a key issue in the understanding of the link between rotation and the presence of chemical peculiarities. \nAims. A sample of 47 low vsini A0−A1 stars (vsini < 65 km s-1), initially selected as main-sequence normal stars, are investigated with high-resolution and high signal-to-noise spectroscopic data. The aim is to detect spectroscopic binaries and chemically peculiar stars, and eventually establish a list of confirmed normal stars. \nMethods. A detailed abundance analysis and spectral synthesis is performed to derive abundances for 14 chemical species. A hierarchical classification, taking measurement errors into account, is applied to the abundance space and splits the sample into two different groups, identified as the chemically peculiar stars and the normal stars. \nResults. We show that about one third of the sample is actually composed of spectroscopic binaries (12 double-lined and five single-lined spectroscopic binaries). The hierarchical classification breaks down the remaining sample into 13 chemically peculiar stars (or uncertain) and 17 normal stars.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".