Database of Accreting Binary Simulations
Bibliographic record
Abstract
We present <strong>DABS</strong> (Database of Accreting Binary Simulations), an open-access database of modelled Low Mass X-ray Binaries (LMXBs). DABS has been created using evolutionary tracks of neutron star and black hole LMXBs, spanning a large set of initial conditions for the accretor mass, donor mass, and orbital period. The LMXBs are evolved with the Convection and Rotation Boosted Magnetic Braking prescription. The most important asset of this online database is the tool <strong>PEAS</strong> (Progenitor Extractor for Accreting Systems) https://github.com/ChatrikMangat/progenlmxb. This tool can be used to predict the progenitors of any user-entered LMXB system and view their properties before the start of mass transfer. This prediction can facilitate preliminary searches for the progenitors of observed LMXBs, which can help in streamlining further detailed analyses. The PEAS tool can also be used to constrain population synthesis techniques that specialize in supernova kicks in binaries and common envelope outcomes.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.450 | 0.003 |
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; both teacher heads agree on what is shown here.
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".