Evolution of the Reactor Antineutrino Flux and Spectrum at Daya Bay
Bibliographic record
Abstract
The Daya Bay experiment has observed correlations between reactor core fuel evolution and changes in the reactor antineutrino flux and energy spectrum. Four antineutrino detectors in two experimental halls were used to identify 2.2 million inverse beta decays (IBDs) over 1230 days spanning multiple fuel cycles for each of six 2.9 GW_{th} reactor cores at the Daya Bay and Ling Ao nuclear power plants. Using detector data spanning effective ^{239}Pu fission fractions F_{239} from 0.25 to 0.35, Daya Bay measures an average IBD yield σ[over ¯]_{f} of (5.90±0.13)×10^{-43} cm^{2}/fission and a fuel-dependent variation in the IBD yield, dσ_{f}/dF_{239}, of (-1.86±0.18)×10^{-43} cm^{2}/fission. This observation rejects the hypothesis of a constant antineutrino flux as a function of the ^{239}Pu fission fraction at 10 standard deviations. The variation in IBD yield is found to be energy dependent, rejecting the hypothesis of a constant antineutrino energy spectrum at 5.1 standard deviations. While measurements of the evolution in the IBD spectrum show general agreement with predictions from recent reactor models, the measured evolution in total IBD yield disagrees with recent predictions at 3.1σ. This discrepancy indicates that an overall deficit in the measured flux with respect to predictions does not result from equal fractional deficits from the primary fission isotopes ^{235}U, ^{239}Pu, ^{238}U, and ^{241}Pu. Based on measured IBD yield variations, yields of (6.17±0.17) and (4.27±0.26)×10^{-43} cm^{2}/fission have been determined for the two dominant fission parent isotopes ^{235}U and ^{239}Pu. A 7.8% discrepancy between the observed and predicted ^{235}U yields suggests that this isotope may be the primary contributor to the reactor antineutrino anomaly.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".