A Study of Compact Object Mergers as Short Gamma‐Ray Burst Progenitors
Bibliographic record
Abstract
We present a theoretical study of double compact objects as potential short/hard gamma-ray burst (GRB) progenitors. An updated population synthesis code StarTrack is used to calculate properties of double neutron stars and black-hole neutron star binaries. We obtain their formation rates, estimate merger times and finally predict their most likely merger locations and afterglow properties for different types of host galaxies. Our results serve for a direct comparison with the recent HETE-II and SWIFT observations of several short bursts, for which afterglows and host galaxies were detected. We also discuss the possible constraints these observations put on the evolutionary models of double compact object formation. We emphasize that our double compact object models can successfully reproduce at the same time short GRBs within both young, star-forming galaxies (e.g., GRB 050709 and GRB 051221A), as well as within old, elliptical hosts (e.g., GRB 050724 and probably GRB 050509B)
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".