Characterization of mini-CryoCube detectors from the RICOCHET experiment commissioning at the Institut Laue-Langevin
Bibliographic record
Abstract
The experiment aims to measure the coherent elastic neutrino-nucleus scattering process from antineutrinos emitted by a research nuclear reactor operated by the Institut Laue-Langevin (Grenoble, France). This article presents a description of the experimental installation and the detector performance achieved during its commissioning with a mini-CryoCube module consisting of three 42-g germanium cryogenic calorimeters. The baseline resolutions and background levels are reported both during reactor-on and reactor-off periods and as noise mitigation techniques were improved. A baseline resolution of 40 eV electron equivalent was achieved for the ionization channel after setup improvements, and the phonon channel resolutions ranged from 50 to 80 eV of total phonon energy. In the energy region from 2 to 7 keV, a nuclear recoil rate of 14 ( 3 ) events / ( kg day keV ) is measured during the reactor-off period selecting events in coincidence with muon veto signals. This rate is in agreement with the cosmogenic neutron rate calculated from GEANT4 simulations. After the rejection of events in coincidence with signals in the muon veto detectors, a combined 90% confidence level limit on the nuclear recoil background of < 9 events / ( kg day keV ) is obtained in that energy region during the reactor-on period, which is compatible with our GEANT4 model calculation corresponding to a total rate of 5 events / ( kg day keV ) . The sensitivity of this analysis was however found to be limited by a surface event contamination which is currently being addressed by the Collaboration with upgraded 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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 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".