Bibliographic record
Abstract
Supersymmetric (SUSY) models with R-parity generically predict sparticle decays with invisible neutralinos, which yield distinctive missing energy events at colliders. Since most LHC searches are designed with this expectation, the putative bounds on sparticle masses become considerably weaker if R-parity is violated so that squarks and gluinos decay to jets with large QCD backgrounds. Here we introduce a scenario in which baryonic R-parity violation (RPV) arises effectively from soft SUSY breaking interactions, but leptonic RPV remains accidentally forbidden to evade constraints from proton decay and FCNCs. The model features a global R-symmetry that initially forbids RPV interactions, a hidden R-breaking sector, and a heavy mediator that communicates this breaking to the visible sector. After R-symmetry breaking, the mediator is integrated out and an effective RPV A-term arises at tree level; RPV couplings between quarks and squarks arise only at loop level and receive additional suppression. Although this mediator must be heavy compared to soft masses, the model introduces no new hierarchy since viable RPV can arise when the mediator mass is near the SUSY breaking scale. In generic regions of parameter space, a light thermally-produced gravitino is stable and can be a viable dark matter candidate.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".