Carbon Abundances of Faint Stars in M13 - Evidence for Two Abundance Altering Mechanisms
Bibliographic record
Abstract
We present an analysis of CH band strengths in Keck LRIS spectra of a sample of 81 stars in M13 within 2 magnitudes of the main-sequence turnoff. The subgiants clearly exhibit a substantial (a factor of ~ 6) spread in [C/Fe]. Moreover, the bulk of the subgiants possess C abundances larger than those found among their more luminous counterparts. The turnoff stars themselves are too warm for appreciable CH formation, but the relatively small range in the observed CH band strength for stars just below the turnoff nevertheless translates into this same spread in [C/Fe]. Still fainter, the sample size is small, but the same range in [C/Fe] appears to be present. On the basis of these observations we suggest that a process external to the present stars has resulted in a substantial star-to-star dispersion in [C/Fe] (and possibly other light elements) among all stars in M13. In addition, the surface C abundances among the more luminous stars have been further modified by the operation of an internal deep-mixing mechanism during red giant branch ascent. The amplitude of the scatter we find in [C/Fe] at all luminosities may prove difficult to explain via accretion from intermediate mass AGB stars as the external "polluting" mechanism.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".