Fragmentation of massive protostellar discs
Bibliographic record
Abstract
We examine whether massive-star accretion discs are likely to fragment due to self-gravity. Rapid accretion and high angular momentum push these discs toward fragmentation, whereas viscous heating and the high protostellar luminosity stabilize them. We find that for a broad range of protostar masses and for reasonable accretion times, massive discs larger than ∼150 au are prone to fragmentation. We develop an analytical estimate for the angular momentum of accreted material, extending the analysis of Matzner & Levin to account for strongly turbulent initial conditions. In a core-collapse model, we predict that discs are marginally prone to fragmentation around stars of about 4–15 M⊙– even if we adopt conservative estimates of the discs' radii and tendency to fragment. More massive stars are progressively more likely to fragment, and there is a sharp drop in the stability of disc accretion at the very high accretion rates expected above 110 M⊙. Fragmentation may starve accretion in massive stars, especially above this limit, and is likely to create swarms of small, coplanar companions.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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".