MaGICC thick disc – I. Comparing a simulated disc formed with stellar feedback to the Milky Way
Bibliographic record
Abstract
We analyse the structure and chemical enrichment of a Milky Way-like galaxy with a stellar mass of 2 × 1010 M⊙, formed in a cosmological hydrodynamical simulation. It is disc dominated with a flat rotation curve, and has a disc scalelength similar to the Milky Way's, but a velocity dispersion that is ∼50 per cent higher. Examining stars in narrow [Fe/H] and [α/Fe] abundance ranges, we find remarkable qualitative agreement between this simulation and observations. (a) The old stars lie in a thickened distribution with a short scalelength, while the young stars form a thinner disc, with scalelengths decreasing, as [Fe/H] increases. (b) Consequently, there is a distinct outward metallicity gradient. (c) Mono-abundance populations exist with a continuous distribution of scaleheights (from thin to thick). However, the simulated galaxy has a distinct and substantive very thick disc (hz ∼ 1.5 kpc), not seen in the Milky Way. The broad agreement between simulations and observations allows us to test the validity of observational proxies used in the literature: we find in the simulation that mono-abundance populations are good proxies for single age populations (<1 Gyr) for most abundances.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".