SPECTRAL ENERGY DISTRIBUTION MAPPING OF TWO ELLIPTICAL GALAXIES ON SUB-kpc SCALES
Bibliographic record
Abstract
ABSTRACT We use high-resolution Herschel-PACS data of two nearby elliptical galaxies, IC 1459 and NGC 2768, to characterize their dust and stellar content. IC 1459 and NGC 2768 have an unusually large amount of dust for elliptical galaxies ((1–3) × 105 ); this dust is also not distributed along the stellar content. Using data from GALEX (ultra-violet) to PACS (far-infrared, FIR), we analyze the spectral energy distribution (SED) of these galaxies with CIGALEMC as a function of the projected position, binning images in 7.″2 pixels. From this analysis, we derive maps of SED parameters, such as the metallicity, the stellar mass, the fraction of young stars, and the dust mass. The larger amount of dust in FIR maps seems related in our model to a larger fraction of young stars which can reach up to 4% in the dustier area. The young stellar population is fitted as a recent (∼0.5 Gyr) short burst of star formation for both galaxies. The metallicities, which are fairly large at the center of both galaxies, decrease with the radial distance with a fairly steep gradient for elliptical 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 | 0.000 |
| 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".