INSPIRE: INvestigating Stellar Population In RElics – V. A catalogue of ultra-compact massive galaxies outside the local Universe and their degree of relicness
Bibliographic record
Abstract
ABSTRACT This paper presents the third data release of the INvestigating Stellar Population In RElics (INSPIRE) project, comprising 52 ultra-compact massive galaxies (UCMGs) observed with the X-Shooter spectrograph. We measure integrated stellar velocity dispersion, [Mg/Fe] abundances, ages, and metallicities for all the INSPIRE objects. We thus infer star formation histories and confirm the existence of a degree of relicness (DoR), defined in terms of the fraction of stellar mass formed by z = 2, the time at which a galaxy has assembled 75 per cent of its mass, and the final assembly time. Objects with a high DoR assembled their stellar mass at early epochs, while low-DoR objects show a non-negligible fraction of later formed populations and hence a spread in ages and metallicities. A higher DoR correlates with larger [Mg/Fe], supersolar metallicity, and larger velocity dispersion values. The 52 UMCGs span a large range of DoR from 0.83 to 0.06, with 38 of them having formed more than 75 per cent of their mass by z = 2. Of these, nine are extreme relics (DoR>0.7), since they formed the totality ($\gt 99~{{\ \rm per\ cent}}$) of their stellar mass by redshift z = 2. The remaining 14 UCMGs cannot be considered relics, as they are characterized by more extended star formation histories. With INSPIRE we built the first sizeable sample of relics outside the local Universe, up to z ∼ 0.4, increasing the number of confirmed relics by a factor of >10, and opening up an important window to explain the mass assembly of massive galaxies in the high-z Universe.
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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 | 0.004 | 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) | 0.001 | 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".