The Gemini Deep Deep Survey. VII. The Redshift Evolution of the Mass‐Metallicity Relation
Bibliographic record
Abstract
We have investigated the mass-metallicity ( M - Z ) relation using galaxies at 0.4 < z < 1.0 from the Gemini Deep Deep Survey (GDDS) and Canada-France Redshift Survey (CFRS). Deep K - and z '-band photometry allowed us to measure stellar masses for 69 galaxies. From a subsample of 56 galaxies, for which metallicity of the interstellar medium is also measured, we identified a strong correlation between mass and metallicity for the first time in the distant universe. This was possible because of the larger baseline spanned by the sample in terms of metallicity (a factor of 7) and mass (a factor of 400) than in previous works. This correlation is much stronger and tighter than the luminosity-metallicity relation, confirming that stellar mass is a more meaningful physical parameter than luminosity. We find clear evidence for temporal evolution in the M - Z relation in the sense that at a given mass, a galaxy at z ~ 0.7 tends to have lower metallicity than a local galaxy of similar mass. We use the z ~ 0.1 Sloan Digital Sky Survey M - Z relation and a small sample of z ~ 2.3 Lyman break galaxies with known mass and metallicity to propose an empirical redshift-dependent M - Z relation. According to this relation the stellar mass and metallicity in small galaxies evolve for a longer time than they do in massive galaxies. This relation predicts that the generally metal-poor damped Lyα galaxies have stellar masses of the order of 10 8.8 M ☉ (with a dispersion of 0.7 dex) all the way from z ~ 0.2 to 4. The observed redshift evolution of the M - Z relation can be reproduced remarkably well by a simple closed-box model in which the key assumption is an e -folding time for star formation that is higher or, in other words, a period of star formation that lasts longer in less massive galaxies than in more massive galaxies. Such a picture supports the downsizing scenario for galaxy formation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".