Where have all the low-metallicity galaxies gone? Tracing evolution in the mass--metallicity plane since a redshift of 0.7
Bibliographic record
Abstract
Even over relatively recent epochs, galaxies have evolved significantly in their location in the mass-metallicity plane, which must be telling us something about the latter stages of galaxy evolution. In this paper, we analyse data from the LEGA-C survey using semi-analytic spectral and photometric fitting to determine these galaxies' evolution up to their observed epoch at $z \sim 0.7$. We confirm that, at $z \sim 0.7$, many objects already lie on the present-day mass-metallicity relation, but with a significant tail of high-mass low-metallicity galaxies that is not seen in the nearby Universe. Similar modelling of the evolution of galaxies in the nearby MaNGA survey allows us to reconstruct their properties at $z \sim 0.7$. Once selection criteria similar to those of LEGA-C are applied, we reassuringly find that the MaNGA galaxies populate the mass-metallicity plane in the same way at $z \sim 0.7$. Matching the LEGA-C sample to their mass-metallicity "twins" in MaNGA at this redshift, we can explore the likely subsequent evolution of individual LEGA-C galaxies. Galaxies already on the present-day mass--metallicity relation form few more stars and their disks fade, so they become smaller and more bulge-like. By contrast, the high-mass low-metallicity galaxies grow their disks through late star formation, and evolve rapidly to higher metallicities due to a cut-off in their wind-driven mass loss. There are significant indications that this late cut-off is associated with the belated end of strong AGN activity in these objects.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".