Measurements of neutrino oscillation in appearance and disappearance channels by the T2K experiment with<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mn>6.6</mml:mn><mml:mo>×</mml:mo><mml:mn>1</mml:mn><mml:msup><mml:mn>0</mml:mn><mml:mn>20</mml:mn></mml:msup></mml:math>protons on target
Bibliographic record
Abstract
We report on measurements of neutrino oscillation using data from the T2K long-baseline neutrino experiment collected between 2010 and 2013. In an analysis of muon neutrino disappearance alone, we find the following estimates and 68% confidence intervals for the two possible mass hierarchies: $\text{normal hierarchy}:\text{ }\text{ }{\mathrm{sin}}^{2}{\ensuremath{\theta}}_{23}=0.51{4}_{\ensuremath{-}0.056}^{+0.055}$ and $\mathrm{\ensuremath{\Delta}}{m}_{32}^{2}=(2.51\ifmmode\pm\else\textpm\fi{}0.10)\ifmmode\times\else\texttimes\fi{}1{0}^{\ensuremath{-}3}\text{ }\text{ }{\mathrm{eV}}^{2}/{c}^{4}$ and $\text{inverted hierarchy}:\text{ }\text{ }{\mathrm{sin}}^{2}{\ensuremath{\theta}}_{23}=0.511\ifmmode\pm\else\textpm\fi{}0.055$ and $\mathrm{\ensuremath{\Delta}}{m}_{13}^{2}=(2.48\ifmmode\pm\else\textpm\fi{}0.10)\ifmmode\times\else\texttimes\fi{}1{0}^{\ensuremath{-}3}\text{ }\text{ }{\mathrm{eV}}^{2}/{c}^{4}$. The analysis accounts for multinucleon mechanisms in neutrino interactions which were found to introduce negligible bias. We describe our first analyses that combine measurements of muon neutrino disappearance and electron neutrino appearance to estimate four oscillation parameters, $|\mathrm{\ensuremath{\Delta}}{m}^{2}|$, ${\mathrm{sin}}^{2}{\ensuremath{\theta}}_{23}$, ${\mathrm{sin}}^{2}{\ensuremath{\theta}}_{13}$, ${\ensuremath{\delta}}_{CP}$, and the mass hierarchy. Frequentist and Bayesian intervals are presented for combinations of these parameters, with and without including recent reactor measurements. At 90% confidence level and including reactor measurements, we exclude the region ${\ensuremath{\delta}}_{CP}=[0.15,0.83]\ensuremath{\pi}$ for normal hierarchy and ${\ensuremath{\delta}}_{CP}=[\ensuremath{-}0.08,1.09]\ensuremath{\pi}$ for inverted hierarchy. The T2K and reactor data weakly favor the normal hierarchy with a Bayes factor of 2.2. The most probable values and 68% one-dimensional credible intervals for the other oscillation parameters, when reactor data are included, are ${\mathrm{sin}}^{2}{\ensuremath{\theta}}_{23}=0.52{8}_{\ensuremath{-}0.038}^{+0.055}$ and $|\mathrm{\ensuremath{\Delta}}{m}_{32}^{2}|=(2.51\ifmmode\pm\else\textpm\fi{}0.11)\ifmmode\times\else\texttimes\fi{}1{0}^{\ensuremath{-}3}\text{ }\text{ }{\mathrm{eV}}^{2}/{c}^{4}$.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".