Elemental abundance analyses with DAO spectrograms: XXXII. HR 6455 (A3 III), <i>δ</i> Aqr (A3 V), <i>η</i> Lep (F2 V), and 1 Boo (A1 V)
Bibliographic record
Abstract
Abstract We examine the sharp‐lined stars HR 6455 (A3 III, v sin i = 8.7 km s–1) and η Lep (F2 V, v sin i = 13.5 km s–1) as well as δ Aqr (A3 V, v sin i = 81 km s–1) and 1 Boo (A1 V, v sin i = 59 km s–1) to increase the number consistently analyzed A and F stars using high dispersion and high S/N (≥200) spectrograms obtained with CCD detectors at the long Coudé camera of the 1.22‐m telescope of the Dominion Astrophysical Observatory. Such studies contribute to understanding systematic abundance differences between normal and non‐magnetic main‐sequence band chemically peculiar A and early F stars. LTE fine analyses of HR 6455, δ Aqr, and 1 Boo using Kurucz's ATLAS suite programs show the same general elemental abundance trends with differences in the metal richness. Light and iron‐peak element abundances are generally solar or overabundant while heavy element and rare earth element abundances are overabundant. HR 6455 is an evolved Am star while δ Aqr and 1 Boo show the phenomenon to different extents. Most derived abundances of η Lep are solar (© 2011 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) | 0.006 | 0.002 |
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".