Phenomenology of left-right supersymmetric models with broken<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mi>B</mml:mi><mml:mi>−</mml:mi><mml:mi>L</mml:mi></mml:math>symmetry
Bibliographic record
Abstract
We discuss the implications of R parity breaking through spontaneous $B\ensuremath{-}L$ breaking in left--right supersymmetric models. We give expressions for three generations of neutrino--neutralino and charged--lepton--chargino mixings. We find the masses of the light neutrinos at both the tree and one loop levels. We explore the most stringent bounds on the parameters of the LRSUSY model coming from rare leptonic processes. These phenomena severely restrict the parameters in both the R-parity violating and R-parity conserving sectors. We find that such models are likely to produce light doubly charged Higgs bosons and fermions, with masses as low as ${M}_{{\ensuremath{\Delta}}^{++},{\stackrel{\ifmmode \tilde{}\else \~{}\fi{}}{\ensuremath{\Delta}}}^{++}}<~200$ GeV for $\mathrm{tan}\ensuremath{\beta}=1;$ however, the right-handed scale is restricted to be heavy, pushing the ${Z}_{R}$ mass above $160$ TeV.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".