Monitoring the SNS basement neutron background with the MARS detector
Bibliographic record
Abstract
Abstract We present the analysis and results of the first dataset collected with the MARS neutron detector deployed at the Oak Ridge National Laboratory Spallation Neutron Source (SNS) for the purpose of monitoring and characterizing the beam-related neutron (BRN) background for the COHERENT collaboration. MARS was positioned next to the COH-CsI coherent elastic neutrino-nucleus scattering detector in the SNS basement corridor. This is the basement location of closest proximity to the SNS target and thus, of highest neutrino flux, but it is also well shielded from the BRN flux by infill concrete and gravel. These data show the detector registered roughly one BRN per day. Using MARS' measured detection efficiency, the incoming BRN flux is estimated to be 1.20 ± 0.56 neutrons/m^2/MWh for neutron energies above ∼3.5 MeV and up to a few tens of MeV. We compare our results with previous BRN measurements in the SNS basement corridor reported by other neutron detectors.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".