RADIO PROPERTIES OF YOUNG STELLAR OBJECTS IN THE CORE OF THE SERPENS SOUTH INFRARED DARK CLOUD
Bibliographic record
Abstract
ABSTRACT We present deep radio continuum observations of the star-forming core of the Serpens South Infrared Dark Cloud with the Karl G. Jansky Very Large Array. Observations were conducted in two bands centered at 7.25 GHz (4.14 cm) and 4.75 GHz (6.31 cm) with a of 8.5 and 11.1 μJy/beam, respectively. We also use 2MASS, Spitzer and Herschel data to put our radio observations in the context of young stellar populations characterized by near and far-infrared observations. Within a 5′ × 5′ region of interest around the central cluster, we detect roughly eighteen radio sources, seven of which we determine are protostellar in nature due to their radio spectral indices and their association with infrared sources. We find evidence for a previously undetected embedded Class 0 protostar and reaffirm Class 0 protostellar classifications determined by previous millimeter wavelength continuum studies. We use our infrared data to derive mid-infrared luminosities for three of our protostellar sources and find relative agreement between the known young stellar object (YSO) radio luminosity versus bolometric luminosity correlation. Lastly, we marginally detect an additional six radio sources at the 2–3σ level that lie within two arcseconds of infrared YSO candidates, providing motivation for higher sensitivity studies to clarify the nature of these sources and further probe embedded and/or low luminosity YSOs in Serpens South.
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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".