Ghosts in the Attic: Mapping the Stellar Content of the S0 Galaxy NGC 5102 12
Bibliographic record
Abstract
The spatial distribution of stars in the nearby S0 galaxy NGC 5102 is investigated using images obtained with WIRCam and MegaCam on the Canada-France-Hawaii Telescope. With the exception of gaps between detector elements, the entire galaxy is surveyed in r ′ and i ′ , while the J and Ks data extend out to RGC ∼ 6 kpc, which corresponds to almost 7 disk scale lengths. A modest population of main sequence (MS) stars with MV < −3.5 and ages ∼ 70 Myr are detected throughout the disk, with the majority located in the southern half of the galaxy. The stellar disk in the northern half of the galaxy is warped, following structure that is also seen in HI. Objects with photometric properties that are consistent with those of bright AGB stars are seen throughout the disk, and the ratio of C stars to bright M giants is consistent with an overall increase in the star formation rate within the past 1 Gyr. Star-forming activity during the interval 0.1 − 2 Gyr was more centrally concentrated than during the past ∼ 100 Myr. The structure of the disk changes near RGC ∼ 5 kpc (5.5 disk scale lengths), in the sense that the radial surface density profile defined by red supergiants (RSGs) and bright AGB stars levels off at larger radii. RSGs and bright AGB stars are traced out to a radius of 14 kpc (15.6 scle lengths) along the southern portion 1 Based on observations obtained with the Megaprime/MegaCam, a joint project of the CFHT and
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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 | 0.001 |
| 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".