A dark seesaw solution to low energy anomalies: MiniBooNE, the muon (g − 2), and BaBar
Bibliographic record
Abstract
A recent update from MiniBooNE has strengthened the observed 4.8σ excess of e-like events. Motivated by this and other notable deviations from standard model predictions, such as the muon (g−2), we propose a solution to low energy anomalies through a dark neutrino sector. The model is renormalizable and can also explain light neutrino masses with an anomaly-free and dark U(1)′ gauge symmetry broken at the GeV scale. Large kinetic mixing leads to s-channel production of heavy neutral leptons at e+e− colliders, where we point out and explain a ≳2σ excess observed in the BaBar monophoton data. Our model is also compatible with anomalous e-like events seen at old accelerator experiments, as well as with an excess of double vertex signatures observed at CCFR.
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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 | 0.000 |
| 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".