THE BLAST SURVEY OF THE VELA MOLECULAR CLOUD: PHYSICAL PROPERTIES OF THE DENSE CORES IN VELA-D
Bibliographic record
Abstract
The Balloon-borne Large-Aperture Submillimeter Telescope (BLAST) carried out a 250, 350, and 500 μm survey of the galactic plane encompassing the Vela Molecular Ridge, with the primary goal of identifying the coldest dense cores possibly associated with the earliest stages of star formation. Here, we present the results from observations of the Vela-D region, covering about 4 deg 2 , in which we find 141 BLAST cores. We exploit existing data taken with the Spitzer MIPS, IRAC, and SEST–SIMBA instruments to constrain their (single-temperature) spectral energy distributions, assuming a dust emissivity index β = 2.0. This combination of data allows us to determine the temperature, luminosity, and mass of each BLAST core, and also enables us to separate starless from protostellar sources. We also analyze the effects that the uncertainties on the derived physical parameters of the individual sources have on the overall physical properties of starless and protostellar cores, and we find that there appear to be a smooth transition from the pre- to the protostellar phase. In particular, for protostellar cores we find a correlation between the MIPS24 flux, associated with the central protostar, and the temperature of the dust envelope. We also find that the core mass function of the Vela-D cores has a slope consistent with other similar (sub)millimeter surveys.
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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 | 0.001 |
| 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".