A spectroscopic survey for <i>λ</i> Bootis stars
Bibliographic record
Abstract
λ Bootis stars comprise only a small number of all A-type stars and are characterized as nonmagnetic, Population i, late B to early F-type dwarfs which show significant underabundances of metals whereas the light elements (C, N, O and S) are almost normal abundant compared to the Sun. In the second paper on a spectroscopic survey for λ Bootis stars, we present the spectral classifications of all program stars observed. These stars were selected on the basis of their Strömgren colors as λ Bootis candidates. In total, 708 objects in six open clusters, the Orion OB1 association and the Galactic field were classified. In addition, 9 serendipity non-candidates in the vicinity of our program stars as well as 15 Guide Star Catalogue stars were observed resulting in a total of 732 classified stars. The 15 objects from the Guide Star Catalogue are part of a program for the classification of apparent variable stars from the Fine Guidance Sensors of the Hubble Space Telescope. A grid of 105 MK standard as well as "pathological" stars guarantees a precise classification. A comparison of our spectral classification with the extensive work of Abt & Morrell ([CITE]) shows no significant differences. The derived types are 0.23 ± 0.09 (rms error per measurement) subclasses later and 0.30 ± 0.08 luminosity classes more luminous than those of Abt & Morrell ([CITE]) based on a sample of 160 objects in common. The estimated errors of the means are ± 0.1 subclasses. The characteristics of our sample are discussed in respect to the distribution on the sky, apparent visual magnitudes and Strömgren colors.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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) | 0.001 | 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".