hep-ph/0701034v2 Group Theoretic Bases for Tribimaximal Mixing
Bibliographic record
Abstract
Present data on neutrino masses and mixing favor the highly symmetric tribimaximal neutrino mixing matrix which suggests an underlying flavor symmetry. A systematic study of non-abelian finite groups of order g ≤ 31 reveals that tribimaximal mixing can be derived not only from the well known flavor symmetry T ≡ A4, the tetrahedral group, but also by using the alternative flavor symmetry (d) T ≡ SL2(F3) ≡ Q4 ˜×Z3, the double tetrahedral group. The double tetrahedral group (d) T does not contain the single tetrahedral group as a subgroup, and has the advantage over it as a flavor symmetry that it can not only underwrite bitrimaximal mixing for neutrinos, equally as well, but also provide a first step to understanding the quark mass hierarchy. Progress in our knowledge of the three neutrino masses and mixings has been remarkable since SuperKamiokande found the first convincing evidence of non zero neutrino mass in 1998 [1], and the Sudbury Neutrino Observatory (SNO) exceeded all expectations by abruptly solving the solar neutrino puzzle in 2001 [2] thereby resolving the 35-year old
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.138 | 0.027 |
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".