Physical structure of the envelopes of intermediate-mass protostars
Bibliographic record
Abstract
Context. Intermediate mass protostars provide a bridge between low- and high-mass protostars. Furthermore, they are an important component of the UV interstellar radiation field. Despite their relevance, little is known about their formation process.Aims. We present a systematic study of the physical structure of five intermediate mass, candidate Class 0 protostars. Our two goals are to shed light on the first phase of intermediate mass star formation and to compare these protostars with low- and high-mass sources.Methods. We derived the dust and gas temperature and density profiles of the sample. We analysed all existing continuum data on each source and modelled the resulting SED with the 1D radiative transfer code DUSTY. The gas temperature was then predicted by means of a modified version of the code CHT96.Results. We found that the density profiles of five out of six studied intermediate mass envelopes are consistent with the predictions of the “inside-out” collapse theory. We compared several physical parameters, like the power law index of the density profile, the size, the mass, the average density, the density at 1000 AU and the density at 10 K of the envelopes of low-, intermediate, and high-mass protostars. When considering these various physical parameters, the transition between the three groups appears smooth, suggesting that the formation processes and triggers do not substantially differ.
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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".