Implications of texture 4 zero lepton mass matrices for
Bibliographic record
Abstract
Lepton mass matrices similar to texture 4 zero quark mass matrices, known to be quite successful in explaining the CKM phenomenology, have been considered for finding the mixing matrix element Ue3 ( ≡ s13) respecting the CHOOZ constraint, with s12 and ∆m2 12 constrained by SNP and s23 and ∆m2 23 constrained by ANP. Taking charged lepton mass matrix Ml to be diagonal, we find that the ranges of s13 corresponding to different SNP solutions very well include the corresponding values of s13 found by Akhmedov et al. by considering neutrino mass matrix Mν with no texture zeros. Considering Ml and Mν both to be real and non-diagonal, s13 ranges for the four SNP solutions come out to be: ∼ 0 − 0.19 (LMA), 0.038 − 0.093 (SMA), 0.042 − 0.095 (LOW), 0.038 − 0.096 (VO), which remain of the same order when Ml and Mν are considered to be complex and non-diagonal. The observation of neutrino oscillations by Super-Kamiokande (SK) [1] as well as by Sudbury Neutrino Observatory (SNO) [2] has provided unambiguous signal for physics beyond the Standard Model (SM). This essentially implies that the neutrinos are massive
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 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".