Tracing the Mass during Low‐Mass Star Formation. I. Submillimeter Continuum Observations
Bibliographic record
Abstract
We have obtained 850 and 450 μm continuum maps of 21 low-mass cores with SEDs ranging from pre-protostellar to Class I (18 K < T bol < 370 K), using SCUBA at the JCMT. In this paper we present the maps, radial intensity profiles, and photometry. Pre-protostellar cores do not have power-law intensity profiles, whereas the intensity profiles of Class 0 and Class I sources can be fitted with power laws over a large range of radii. A substantial number of sources have companion sources within a few arcminutes (two out of five pre-protostellar cores, nine out of 16 Class 0/I sources). The mean separation between sources is 10,800 AU. The median separation is 18,000 AU including sources without companions as a lower limit. The mean value of the spectral index between 450 and 850 μm is 2.8 ± 0.4, with pre-protostellar cores having slightly lower spectral indices (2.5 ± 0.4). The mean mass of the sample, based on the dust emission in a 120'' aperture, is 1.1 ± 0.9 M ☉ . For the sources fitted by power-law intensity distributions ( I ν ( b )/ I ν (0) = ( b / b 0 ) m ), the mean value of m is 1.52 ± 0.45 for Class 0 and I sources at 850 μm and 1.44 ± 0.25 at 450 μm. Based on a simple analysis, assuming the emission is in the Rayleigh-Jeans limit and that T d ( r ) ∝ r -0.4 , these values of m translate into power-law density distributions ( n ∝ r - p ) with p ~ 2.1. However, we show that this result may be changed by more careful consideration of effects such as beam size and shape, finite outer radii, more realistic T d ( r ), and failure of the Rayleigh-Jeans approximation.
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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 | 0.000 |
| 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".