Near infrared spectroscopy of starburst galaxies
Bibliographic record
Abstract
(Abridged) We present new K-band spectroscopy for a sample of 48 starburst galaxies, obtained using UKIRT in Hawaii. This constitutes a fair sample of the most common types of starburst galaxies found in the nearby Universe. The variety of near infrared spectral features shown by these galaxies implies different bursts characteristics, which suggests that we survey galaxies with different star formation histories or at different stages of their burst evolution. Using synthetic starburst models, we conclude that the best ensemble of parameters which describe starburst galaxies in the nearby universe are a constant rate of star formation, a Salpeter IMF with an upper mass cutoff equal to 30 solar mass and bursts ages between 10 Myr and 1 Gyr. The model is fully consistent with the differences observed in the optical and FIR between the different types of starbursts. It suggests that HII galaxies have younger bursts and lower metallicities than SBNGs, while LIRGs have younger bursts but higher metallicities. Our observations suggest that the starburst phenomenon must be a sustained or self--sustained phenomenon: either star formation is continuous in time or multiple bursts happen in sequence over a relatively long period of time. The generality of our observations implies that this is a characteristic of starburst galaxies in the nearby 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 | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".