Testing the chemical homogeneity of chemically tagged dissolved birth clusters
Bibliographic record
Abstract
ABSTRACT Chemically tagging stars back to common formation sites in the Milky Way and establishing a high level of chemical homogeneity in these chemically tagged birth clusters is crucial for understanding the chemical and dynamical history of the Galactic disc. We constrain the intrinsic abundance scatter in 17 newly chemically tagged dissolved birth clusters found in the APOGEE survey by modelling APOGEE spectra as a one-dimensional function of initial stellar mass, performing forward modelling of the observed stellar spectra, then comparing the data and simulations using Approximate Bayesian Computation. We exemplify this method with the well-known open clusters M67, NGC 6819, and NGC 6791. We study 15 elements measured by APOGEE and find that, in general, we are able to obtain very strong constraints on the intrinsic abundance scatter of most elements in the chemically tagged birth clusters, with upper limits of ≲0.02 dex for C, ≲0.03 dex for O, Mn, and Fe, ≲0.04 dex for Si and Ni, and ≲0.05 dex for N, Mg, and Ca. While we find some evidence for a small amount of chemical inhomogeneity in the remaining elements (i.e. Na, Al, S, K, Ti, and V), we are still able to obtain similar or stronger limits compared to those found for open clusters, consistent with previous findings. By strongly constraining their level of chemical homogeneity, we can strengthen the statement that these groups of stars represent birth clusters, with promising implications for future chemical tagging studies.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".