Elemental abundance analyses with DAO spectrograms: XL
Bibliographic record
Abstract
We continue our series of high‐quality fine analyses of slowly and moderately rotating normal and peculiar Main Sequence Band B, A, and F stars. We use Kurucz's ATLAS9 model atmospheres in Local Thermodynamic Equilibrium and WIDTH9 codes and high signal‐to‐noise (>200) spectrograms currently obtained with a charge‐coupled device detectors on the long camera of the Coudé spectrograph of the 1.22‐m telescope of the Dominion Astrophysical Observatory. We were surprised that the elemental abundances of the A2 V star HR 196 indicated that it was slightly metal‐poor relative to the Sun. Its projected rotational velocity is 36±2 km s−1. Its abundances are for the most part close to those of α Dra (A0 III), a star with less than solar abundances. We found that the B8 V star HR 6968 ( km s−1) was a peculiar member of the HgMn class with elemental abundances somewhat similar to those of 53 Tau. Most significantly, it has an overabundance of Mn, and Hg II λ3984 is absent. Our analysis of the sharp‐lined ( km s−1) HgMn star HR 7664 is an improvement of the earlier co‐added photographic study of this series, with reduced scatter about the mean abundance for each atomic species. Further, we found abundances for several additional atomic species including Xe II.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.028 | 0.011 |
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".