1 A three stage model for the inner engine of GRBs: Prompt emission and early afterglow
Bibliographic record
Abstract
We describe a model within the "quark-nova" scenario to interpret the recent observations of early X-ray afterglows of long gamma-ray bursts (GRBs) with the Swift satellite. This is a three-stage model within the context of a core-collapse supernova. STAGE 1 is an accreting (proto-) neutron star leading to a possible delay between the core collapse and the GRB. STAGE 2 is accretion onto a quark star, launching an ultrarelativistic jet generating the prompt GRB. This jet also creates the afterglow as the jet interacts with the surrounding medium creating an external shock. Slower shells ejected from the quark star (during accretion), can re-energize the external shock leading to a flatter segment in the X-ray afterglow. STAGE 3, which occurs only if the quark star collapses to form a black hole, consists of an accreting black hole. The jet launched in this accretion process interacts with the preceding quark star jet, and could generate the flaring activity frequently seen in early X-ray afterglows. Alternatively, a STAGE 2b can occur in our model if the quark star does not collapse to a black hole. The quark star in this case can then spin down due to magnetic braking, and the spin down energy may lead to flattening in the X-ray afterglow as well. This model seems to account for both the energies and the timescales of GRBs, in addition to the newly discovered early X-ray afterglow features.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.005 |
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".