A<i>SPITZER</i>SEARCH FOR COLD DUST WITHIN GLOBULAR CLUSTERS
Bibliographic record
Abstract
Globular cluster (GC) stars evolving off the main sequence are known to lose mass, and it is expected that some of the lost material should remain within the cluster as an intracluster medium (ICM). Most attempts to detect such an ICM have been unsuccessful. The Multiband Imaging Photometer for Spitzer on the Spitzer Space Telescope was used to observe eight Galactic GCs in an attempt to detect the thermal emission from ICM dust. Most clusters do not have significant detections at 70 μm; one cluster, NGC 6341, has tentative evidence for the presence of dust, but 90 μm observations do not confirm the detection. Individual 70 μm point sources which appear in several of the cluster images are likely to be background galaxies. The inferred dust mass and upper limits are less than 4 × 10 −4 M ☉ , well below expectations for cluster dust production from mass loss in red and asymptotic giant branch stars. This implies that either GC dust production is less efficient, or that ICM removal or dust destruction is more efficient, than previously believed. We explore several possibilities for ICM removal and conclude that present data do not yet permit us to distinguish between them.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.004 | 0.001 |
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".