MaGICC discs: matching observed galaxy relationships over a wide stellar mass range
Bibliographic record
Abstract
We use the same physical model to simulate four galaxies that match the relation between stellar and total mass, over a mass range that includes the vast majority of disc galaxies. The resultant galaxies, part of the Making Galaxies in a Cosmological Context (MaGICC) programme, also match observed relations between luminosity, rotation velocity, size, colour, star formation rate, H i mass, baryonic mass and metallicity. Radiation energy feedback from massive stars and supernova energy balance the complex interplay between cooling gas, regulated star formation, large-scale outflows and recycling of gas in a manner which correctly scales with the mass of the galaxy. Outflows, driven by the expansion of shells and superbubbles of overlapping supernova explosions, also play a key role in simulating galaxies with exponential surface brightness profiles, flat rotation curves and dark matter cores. Our study implies that large-scale outflows are the primary driver of the dependence of disc galaxy properties on mass. We show that the degree of outflows invoked in our model is required to meet the constraints provided by observations of O vi absorption lines in the circumgalactic media of nearby 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".