Weighing in on black hole binaries with bpass: LB-1 does not contain a 70 M⊙ black hole
Bibliographic record
Abstract
ABSTRACT The recent identification of a candidate very massive (70 M⊙) black hole (BH) is at odds with our current understanding of stellar winds and pair-instability supernovae. We investigate alternate explanations for this system by searching the bpass v2.2 stellar and population synthesis models for those that match the observed properties of the system. We find binary evolution models that match the LB-1 system, at the reported Gaia distance, with more moderate BH masses of 4–7 M⊙. We also examine the suggestion that the binary motion may have led to an incorrect distance determination by Gaia. We find that the Gaia distance is accurate and that the binary system is consistent with the observation at this distance. Consequently, it is highly improbable that the BH in this system has the extreme mass originally suggested. Instead, it is more likely to be representative of the typical BH binary population expected in our Galaxy.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".