Absence of the predicted 2022 October outburst of OJ 287 and implications for binary SMBH scenarios
Bibliographic record
Abstract
ABSTRACT The project MOMO (Multiwavelength Observations and Modelling of OJ 287) was set up to test predictions of binary supermassive black hole (SMBH) scenarios and to understand disc–jet physics of the blazar OJ 287. After a correction, the precessing binary (PB) SMBH model predicted the next main outburst of OJ 287 in 2022 October, making the outburst well observable and the model testable. We have densely covered this period in our ongoing multifrequency radio, optical, ultraviolet (UV), and X-ray monitoring. The predicted outburst was not detected. Instead, OJ 287 was at low optical–UV emission levels, declining further into November. The predicted thermal bremsstrahlung spectrum was not observed either, at any epoch. Further, applying scaling relations, we estimate an SMBH mass of OJ 287 of 108 M⊙. The latest in a sequence of deep low states that recur every 1–2 yr is used to determine an upper limit on the Eddington ratio and on the accretion-disc luminosity. This limit is at least a factor of 10 lower than required by the PB model with its massive primary SMBH of >1010 M⊙. All these results favour alternative binary SMBH models of OJ 287 that require neither strong orbital precession nor a very large mass of the primary SMBH.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".