The imprint of clump formation at high redshift – I. A disc α-abundance dichotomy
Bibliographic record
Abstract
The disc structure of the Milky Way is marked by a chemical dichotomy, with high-α and low-α abundance sequences, traditionally identified with the geometric thick and thin discs. This identification is aided by the old ages of the high-α stars, and lower average ages of the low-α ones. Recent large-scale surveys such as APOGEE have provided a wealth of data on this chemical structure, including showing that an identification of chemical and geometric thick discs is not exact, but the origin of the chemical dichotomy has remained unclear. Here we demonstrate that a dichotomy arises naturally if the early gas-rich disc fragments, leading to some fraction of the star formation occuring in clumps of the type observed in high-redshift galaxies. These clumps have high star formation rate density. They therefore enrich rapidly, moving from the low-α to the high-α sequence, while more distributed star formation produces the low-α sequence. We demonstrate that this model produces a chemically defined thick disc that has many of the properties of the Milky Way’s thick disc. Because clump formation is common in high-redshift galaxies, we predict that chemical bimodalities are common in massive galaxies.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".