Class 0 Protostars in the Perseus Molecular Cloud: A Correlation Between the Youngest Protostars and the Dense Gas Distribution
Bibliographic record
Abstract
We use PACS and SPIRE continuum data at 160 µm, 250 µm, 350 µm, and 500 µm from the Herschel Gould Belt Survey to sample seven clumps in Perseus: B1, B1-E, B5, IC348, L1448, L1455, and NGC1333. Additionally, we identify and characterize the embedded Class 0 protostars using detections of compact Herschel sources at 70 µm as well as archival Spitzer catalogues and SCUBA 850 µm photometric data. We identify 28 candidate Class 0 protostars, four of which are newly discovered sources not identified with Spitzer. We find that the star formation efficiency of clumps, as traced by Class 0 protostars, correlates strongly with the flatness of their respective column density distributions at high values. This correlation suggests that the fraction of high column density material in a clump reflects only its youngest protostellar population rather than its entire source population. We propose that feedback from either the formation or evolution of protostars changes the local density structure of clumps.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".