Phenomenology of a 5D orbifold<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:msub><mml:mrow><mml:mi>SU</mml:mi><mml:mo>(</mml:mo><mml:mn>3</mml:mn><mml:mo>)</mml:mo><mml:mn/></mml:mrow><mml:mrow><mml:mi>W</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math>unification model
Bibliographic record
Abstract
We study the phenomenology of a 5D ${\mathrm{SU}(3)}_{W}$ model on an ${S}_{1}{/(Z}_{2}\ifmmode\times\else\texttimes\fi{}{Z}_{2}^{\ensuremath{'}})$ orbifold in which the minimal scalar sector plays the essential role of radiatively generating neutrino Majorana masses without the benefit of right-handed singlets. We carefully examine how the exotic scalars affect the renormalization group equations for the gauge couplings and the 5D ${\mathrm{SU}(3)}_{W}$ unification. We find that the compactification scale of the extra dimension is in the range of $1/R\ensuremath{\sim}1.5--5\mathrm{TeV}.$ The possibility of the existence of relatively low mass Kaluza-Klein excitations makes the phenomenology of the near term of interest. Some possible bilepton signatures can be searched for in future colliders and in neutrino scattering experiments with intense neutrino beams. The low energy constraints from muon physics and the lepton number violating decay process induced by the bilepton are also discussed. These constraints can provide new information about the structure of Yukawa couplings which might be useful for future model building.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".