Bibliographic record
Abstract
ABSTRACT Supermassive stars have been proposed as the progenitors of the massive ($\sim \!10^{9}\, \mathrm{M}_{\odot }$) quasars observed at z ∼ 7. Prospects for directly detecting supermassive stars with next-generation facilities depend critically on their intrinsic lifetimes, as well as their formation rates. We use the one-dimensional stellar evolution code kepler to explore the theoretical limiting case of zero-metallicity non-rotating stars, formed monolithically with initial masses between $10$ and $190\, \mathrm{kM}_{\odot }$. We find that stars born with masses between $\sim\! 60$ and $\sim\! 150\, \mathrm{kM}_{\odot }$ collapse at the end of the main sequence, burning stably for $\sim\! 1.5\, \mathrm{Myr}$. More massive stars collapse directly through the general relativistic instability after only a thermal time-scale of $\sim\! 3$–$4\, \mathrm{kyr}$. The expected difficulty in producing such massive thermally relaxed objects, together with recent results for currently preferred rapidly accreting formation models, suggests that such ‘truly direct’ or ‘dark’ collapses may not be typical for supermassive objects in the early Universe. We close by discussing the evolution of supermassive stars in the broader context of massive primordial stellar evolution and the possibility of supermassive stellar explosions.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".