CHEMICAL TAGGING IN THE SDSS-III/APOGEE SURVEY: NEW IDENTIFICATIONS OF HALO STARS WITH GLOBULAR CLUSTER ORIGINS
Bibliographic record
Abstract
ABSTRACT We present new identifications of five red giant stars in the Galactic halo with chemical abundance patterns that indicate they originally formed in globular clusters. Using data from the Apache Point Observatory Galactic Evolution Experiment (APOGEE) Survey available through Sloan Digital Sky Survey (SDSS) Data Release 12, we first identify likely halo giants, and then search those for the well-known chemical tags associated with globular clusters, specifically enrichment in nitrogen and aluminum. We find that 2% of the halo giants in our sample have this chemical signature, in agreement with previous results. Following the interpretation in our previous work on this topic, this would imply that at least 13% of halo stars originally formed in globular clusters. Recent developments in the theoretical understanding of globular cluster formation raise questions about that interpretation, and we concede the possibility that these migrants represent a small fraction of the halo field. There are roughly as many stars with the chemical tags of globular clusters in the halo field as there are in globular clusters, whether or not they are accompanied by a much larger chemically untaggable population of former globular cluster stars.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".