The star-formation histories of early-type galaxies from ATLAS<sup>3D</sup>
Bibliographic record
Abstract
Abstract We present an exploration of the integrated stellar populations of early-type galaxies (ETGs) from the ATLAS3D survey. We use two approaches: firstly the application of line-indices interpreted through single stellar population (SSP) models, which provide a single value of age, metallicity and abundance ratio. And secondly, by fitting a linear combination of SSP spectra to our data, smoothly weighted in the free parameters of age and metallicity, thereby inferring a star-formation history of these galaxies. Despite the significant differences in these approaches, we obtain generally consistent results, such that galaxies that are more massive appear older with enhanced abundance ratios using line indices, and have shorter star-formation histories weighted to early times. We highlight two limitations of the index-SSP approach. Firstly the SSP-equivalent ages belie the fact that ETGs are overwhelmingly composed of ancient stars. Secondly, the young stellar contributions implied in our star formation histories are required to obtain realistic UV-optical colours. We remark that, even fitting solar-abundance models, we can recover a star-formation duration that correlates with the measured alpha-enhancement, in agreement with other recent work.
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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 | 0.002 |
| 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) | 0.002 | 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".