Galaxy pairs in the Sloan Digital Sky Survey – XIV. Galaxy mergers do not lie on the fundamental metallicity relation
Bibliographic record
Abstract
ABSTRACT In recent observational studies, star-forming galaxies have been shown to follow a relation often dubbed the fundamental metallicity relation (FMR). This relation links the stellar mass of a galaxy with its star formation rate (SFR) and its gas-phase metallicity. Specifically, the FMR predicts that galaxies, at a given stellar mass, exhibit lower metallicities for higher SFRs. This trend is qualitatively consistent with observations of galaxy pairs, which have been robustly shown to experience increasing gas-phase metallicity dilution and enhanced star formation activity with decreasing projected separation. In this work, we show that, despite the qualitative consistency with FMR expectations, the observed O/H dilution in galaxy pairs of the Sloan Digital Sky Survey is stronger than what is predicted by the FMR. We conclude that the evolutionary phase of galaxies interacting with companions is not encoded in the FMR, and thus, mergers constitute a clearly defined population of outliers. We find that galaxies in pairs are consistent with the FMR only when their separation is larger than 110 kpc. Finally, we also quantify the local environment of the pairs using the number of galaxy neighbours within 2 Mpc, N2, and the projected separation to the second closest galaxy, r2. We find that pairs are more sensitive to a second companion than to the local galaxy density, displaying less elevated SFRs with smaller values of r2.
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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 | 0.001 |
| Research integrity | 0.000 | 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".