Imaging of mgb starbursts - II. The nature of the sample
Bibliographic record
Abstract
In this paper, broad-band imaging in BVRI is used in parallel with information from long-slit spectroscopy and IRAS data to study star formation processes in a sample of 15 MBG (Montreal blue galaxy) starbursts, in order to understand their nature more clearly. Most of these galaxies are early-type spirals with disturbed morphologies. The burst of star formation is concentrated in the nucleus, extending to a mean distance of 1.6 kpc from the centre. In the most active cases, ionized gas could be detected up to a substantial fraction of the radius of the optical surface of the galaxy. We have found evidence suggesting that the enhancement of star formation in our galaxies is correlated to a higher concentration of gas in the nucleus. No mechanism was clearly identified to explain the accretion of gas in this region. Even though we see MBGs at different leveis of activity and with different morphologies, they present similar characteristics in terms of star formation processes. The peculiar morphologies, the infrared characteristics and the net excess of gas in the MBGs compared with galaxies of the same morphological type suggest that the bursts are related to some kind of interaction with other galaxies. We found near constant star formation rates over a period of a few Gyr, which we interpret as an indication of either long duration bursts ( time-scale of the order 1Gyr} or a succession of shorter bursts. The concentration of the bursts into the circumnuclear regions and their importance in terms of masses of stars created suggest that this particular phenomenon could represent an important phase in the evolution of these galaxies.
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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 | 0.001 | 0.000 |
| 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".