A CHANDRA ACIS STUDY OF THE YOUNG STAR CLUSTER TRUMPLER 15 IN CARINA AND CORRELATION WITH NEAR-INFRARED SOURCES
Bibliographic record
Abstract
ABSTRACT Using the highest-resolution X-ray observation of the Trumpler 15 star cluster taken by the Chandra X-ray Observatory , we estimate the total size of its stellar population by comparing the X-ray luminosity function (XLF) of the detected sources to a calibrator cluster and identify for the first time a significant fraction (∼14%) of its individual members. The highest-resolution near-IR observation of Trumpler 15 (taken by the HAWK-I instrument on the Very Large Telescope) was found to detect most of our X-ray selected sample of cluster members, with a K -excess disk frequency of 3.8% ± 0.7%. The near-IR data, XLF, and published spectral types of the brightest members support a cluster age estimate (5–10 Myr) that is older than those for the nearby Trumpler 14 and Trumpler 16 clusters, and suggest that high-mass members may have already exploded as supernovae. The morphology of the inner ∼0.7 pc core of the cluster is found to be spherical. However, the outer regions (beyond ∼2 pc) are elongated, forming an “envelope” of stars that, in projection, appears to connect Trumpler 15 to Trumpler 14; this morphology supports the view that these clusters are physically associated. Clear evidence of mass segregation is seen. This study appears in this special issue devoted to the Chandra Carina Complex Project, a 1.42 deg 2 Chandra X-ray survey of the Great Nebula in Carina.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".