The Mass Distribution and Lifetime of Prestellar Cores in Perseus, Serpens, and Ophiuchus
Bibliographic record
Abstract
We present an unbiased census of starless cores in Perseus, Serpens, and Ophiuchus, assembled by comparing large-scale Bolocam 1.1 mm continuum emission maps with Spitzer c2d surveys. We use the c2d catalogs to separate 108 starless from 92 protostellar cores in the 1.1 mm core samples from Enoch and Young and their coworkers. A comparison of these populations reveals the initial conditions of the starless cores. Starless cores in Perseus have similar masses but larger sizes and lower densities on average than protostellar cores, with sizes that suggest density profiles substantially flatter than ρ ∝ r −2 . By contrast, starless cores in Serpens are compact and have lower masses than protostellar cores; future star formation will likely result in lower mass objects than the currently forming protostars. Comparison to dynamical masses estimated from the NH 3 survey of Perseus cores by Rosolowsky and coworkers suggests that most of the starless cores are likely to be gravitationally bound, and thus prestellar. The combined prestellar core mass distribution includes 108 cores and has a slope of α = − 2.3 ± 0.4 for M > 0.8 M ☉ . This slope is consistent with recent measurements of the stellar initial mass function, providing further evidence that stellar masses are directly linked to the core formation process. We place a lower limit on the core-to-star efficiency of 25%. There are approximately equal numbers of prestellar and protostellar cores in each cloud; thus the dense prestellar core lifetime must be similar to the lifetime of embedded protostars, or 4.5 × 10 5 yr, with a total uncertainty of a factor of 2. Such a short lifetime suggests a dynamic, rather than quasi-static, core evolution scenario, at least at the relatively high mean densities ( n > 2 × 10 4 cm −3 ) to which we are sensitive.
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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 | 0.002 | 0.001 |
| 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".