ISM properties in low-metallicity environments
Bibliographic record
Abstract
We present new 450 and 850 μm SCUBA data of the dwarf galaxy NGC 1569. We construct the mid-infrared to millimeter SED of NGC 1569, using ISOCAM, ISOPHOT, IRAS, KAO, SCUBA and MAMBO data, and model the SED in order to explore the nature of the dust in low metallicity environments. The detailed modeling is performed in a self-consistent way, synthesizing the global ISRF of the galaxy using an evolutionary synthesis model with further constraints provided by the observed MIR ionic lines and a photoionisation model. Our results show that the dust properties are different in this low metallicity galaxy compared to other more metal rich galaxies. The results indicate a paucity of PAHs probably due to the destructive effects of the ISRF penetrating a clumpy environment and a size-segregation of grains where the emission is dominated by small grains of size ~, consistent with the idea of shocks having a dramatic effect on the dust properties in NGC 1569. A significant millimetre excess is present in the dust SED which can be explained by the presence of ubiquitous very cold dust ( K). This dust component accounts for 40 to 70% of the total dust mass in the galaxy ( ) and could be distributed in small clumps (size a few pc) throughout the galaxy. We find a gas-to-dust mass ratio of 740-1600, larger than that of the Galaxy and a dust-to-metals ratio of to . We generate an extinction curve for NGC 1569, consistent with the modeled dust size distribution. This extinction curve has relatively steep FUV rise and smaller 2175 Å bump, resembling the observed extinction curve of some regions in the Large Magellanic Cloud.
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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 | 0.000 | 0.000 |
| 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) | 0.001 | 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".