Correlated backgrounds for near-surface Inverse Beta Decay detectors
Bibliographic record
Abstract
Aboveground antineutrino detection requires careful control of cosmogenic background sources and accurate quantification of any residual backgrounds that survive an Inverse Beta Decay (IBD) event selection. Cosmic high-energy neutrons are among the most prominent sources of background since their flux is relatively high at the Earth’s surface. The PROSPECT detector (Precision Reactor Oscillation and SPECTrum) was deployed at less than 10 m distance from the High Flux Isotope Reactor at Oak Ridge National Laboratory and has demonstrated successful aboveground antineutrino measurements with a signal-to-background ratio greater than 1:1. A detailed Monte Carlo simulation code was developed to match the performance of PROSPECT during the reactor off period when only residual backgrounds are measured. In addition to illuminating the characteristics of these residual backgrounds, this code allows us to examine the performance of a variety of notional shielding and detector configurations. In this work, we describe the performance of compact shielding configurations to provide input on cosmic neutron background reduction for future aboveground antineutrino detector designs. This work is supported by the US DOE Office of High Energy Physics, the Heising-Simons Foundation, CFREF and NSERC of Canada, and internal investments at all institutions, and by the U.S. Department of Energy National Nuclear Security Administration and Lawrence Livermore National Laboratory [Contract No. DE-AC52-07NA27344, release number LLNL-ABS-832544].
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".