The evolutionary status of high and extremely low surface brightness dwarf galaxies
Bibliographic record
Abstract
Studying dwarf galaxies can shed light on the original building blocks of galaxy formation. Most large galaxies are thought to be built up over billions of years through the collisions and mergers of smaller galaxies. The dwarf galaxies we see today are the evolved remnants of those building blocks, and by understanding their nature and evolution, we can study the raw ingredients of galaxy formation. Blue Compact Dwarf galaxies (BCDs) and Almost Dark galaxies are at opposite extremes of today's population of dwarf galaxies. BCDs are exceptionally compact and host very intense starbursts, while Almost Dark galaxies are much more diffuse and have weak stellar populations. This work studies the evolutionary context of BCDs by using deep, high-resolution images to study the detailed structure of their components, and by fitting our multi-wavelength observations with models to describe the properties of their stars, gas, and dust. BCDs appear to have exceptionally compact old stellar populations and unusually large star formation rates, when compared to typical dwarf galaxies. By contrast, the optically faint, gas-dominated Almost Dark galaxies have extremely low star formation rates and weak stellar populations. In particular, one of the Almost Darks studied in this work has very unusual properties and is in disagreement with widely-studied scaling relations for large samples of galaxies. It appears to have too little stellar mass, a distribution of HI that is too extended to be supported by its modest rotation, and the highest well-measured gas mass-to-light ratio ever observed. These two extreme classes may represent evolutionary stages that all galaxies pass through, and appear to be extreme ends of the broad continuum of dwarf galaxy properties. In order to use today's dwarf galaxies as windows into the building blocks of early galaxy formation, these unusual states and evolutionary pathways must be understood.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".