Elemental abundance analyses with DAO spectrograms: XXXI. The early F supergiants <i>ν</i> Her (F2 II) and 41 Cyg (F5 Ib‐II)
Bibliographic record
Abstract
Abstract This series of high quality elemental abundance analyses of mostly Main Sequence normal and peculiar B, A, and F stars defines their properties and provides data for the comparison with analyses of somewhat similar stars and with theoretical predictions. Most use high dispersion and high S/N (≥ 200) spectrograms obtained with CCD detectors at the long camera of the 1.22‐m Dominion Astrophysical Observatory telescope's coudé spectrograph. Here we expand the range of stars examined to include two relatively quiescent F supergiants. ν Her (F2 II) and 41 Cyg (F5 Ib‐II) are analyzed as consistently as possible with previous studies. These LTE fine analyses use the ATLAS9 and the WIDTH9 programs of R. L. Kurucz. High signal‐to‐noise spectrograms and high quality atomic data were employed. The derived values of these photometrically constant stars are somewhat different with the abundances of ν Her being somewhat metal‐poor and those of 41 Cyg being crudely solar‐like. Our analyses indicate that the basic results of Luck & Wepfer (1995) who also studied ν Her and 41 Cyg are not likely to be significantly changed by new studies of all their stars. (© 2008 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
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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) | 0.005 | 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".