The low-mass content of the massive young star cluster RCW 38
Bibliographic record
Abstract
RCW 38 is a deeply embedded young (∼1 Myr), massive star cluster located at a distance of 1.7 kpc. Twice as dense as the Orion nebula cluster, orders of magnitude denser than other nearby star-forming regions and rich in massive stars, RCW 38 is an ideal place to look for potential differences in brown dwarf formation efficiency as a function of environment. We present deep, high-resolution adaptive optics data of the central ∼0.5 × 0.5 pc2 obtained with NACO at the Very Large Telescope. Through comparison with evolutionary models, we determine masses and extinction for ∼480 candidate members, and derive the first initial mass function (IMF) of the cluster extending into the substellar regime. Representing the IMF as a set of power laws in the form dN/dM ∝ M−α, we derive the slope α = 1.60 ± 0.13 for the mass range 0.5–20 M⊙,which is shallower than the Salpeter slope, but in agreement with results in several other young massive clusters. At the low-mass side, we find α = 0.71 ± 0.11 for masses between 0.02 and 0.5 M⊙, or α = 0.81 ± 0.08 for masses between 0.02 and 1 M⊙. Our result is in agreement with the values found in other young star-forming regions, revealing no evidence that a combination of high stellar densities and the presence of numerous massive stars affects the formation efficiency of brown dwarfs and very-low-mass stars. We estimate that the Milky Way galaxy contains between 25 and 100 billion brown dwarfs (with masses >0.03 M⊙).
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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 | 0.001 |
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".