WATCHDOG: A Comprehensive All-Sky Database of Galactic Black Hole X-ray Binaries
Bibliographic record
Abstract
With the advent of more sensitive all-sky instruments, the transient Universe is being probed in greater depth than ever before. Taking advantage of available resources, we have established a comprehensive database of black hole (and black hole candidate) X-ray binary (BHXB) activity between 1996 and 2015 as revealed by all-sky instruments, scanning surveys, and select narrow-field X-ray instruments aboard the INTErnational Gamma-Ray Astrophysics Laboratory (INTEGRAL), Monitor of All-Sky X-ray Image (MAXI), Rossi X-ray Timing Explorer (RXTE), and Swift telescopes; the Whole-sky Alberta Time-resolved Comprehensive black-Hole Database Of the Galaxy or WATCHDOG. Over the past two decades, we have detected 132 transient outbursts, tracked and classified behavior occurring in 47 transient and 10 persistently accreting BHs, and performed a statistical study on a number of outburst properties across the Galactic population. We find that outbursts undergone by BHXBs that do not reach the thermally dominant accretion state make up a substantial fraction ($\sim$ 40%) of the Galactic transient BHXB outburst sample over the past $\sim20$ years. Our findings suggest that this "hard-only" behavior, observed in transient and persistently accreting BHXBs, is neither a rare nor recent phenomenon and may be indicative of an underlying physical process, relatively common among binary BHs, involving the mass-transfer rate onto the BH remaining at a low level rather than increasing as the outburst evolves. We discuss how the larger number of these "hard-only" outbursts and detected outbursts in general have significant implications for both the luminosity function and mass-transfer history of the Galactic BHXB population.
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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 | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".