Measurement of the Inclusive Electron Neutrino Charged Current Cross Section on Carbon with the T2K Near Detector
Bibliographic record
Abstract
The T2K off-axis near detector ND280 is used to make the first differential cross-section measurements of electron neutrino charged current interactions at energies $\ensuremath{\sim}1\text{ }\mathrm{GeV}$ as a function of electron momentum, electron scattering angle, and four-momentum transfer of the interaction. The total flux-averaged ${\ensuremath{\nu}}_{e}$ charged current cross section on carbon is measured to be $⟨\ensuremath{\sigma}{⟩}_{\ensuremath{\phi}}=1.11\ifmmode\pm\else\textpm\fi{}0.10(\text{stat})\ifmmode\pm\else\textpm\fi{}0.18(\text{syst})\ifmmode\times\else\texttimes\fi{}1{0}^{\ensuremath{-}38}\text{ }\text{ }{\mathrm{cm}}^{2}/\text{nucleon}$. The differential and total cross-section measurements agree with the predictions of two leading neutrino interaction generators, NEUT and GENIE. The NEUT prediction is $1.23\ifmmode\times\else\texttimes\fi{}1{0}^{\ensuremath{-}38}\text{ }\text{ }{\mathrm{cm}}^{2}/\text{nucleon}$ and the GENIE prediction is $1.08\ifmmode\times\else\texttimes\fi{}1{0}^{\ensuremath{-}38}\text{ }\text{ }{\mathrm{cm}}^{2}/\text{nucleon}$. The total ${\ensuremath{\nu}}_{e}$ charged current cross-section result is also in agreement with data from the Gargamelle experiment.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".