A study on the wall effect of the Spherical Proportional Counter for long-range particle detection
Bibliographic record
Abstract
The Spherical Proportional Counter is a large-volume gaseous detector that finds application in many fields, like α, β, γ radiation detection, neutrino detection and Dark Matter research. When a reaction happens close to the detector wall it is possible for the produced particles to hit the wall and lose energy. This is known as the wall effect and it leads to wrong calculations of the incident particle energy. It depends on the particles’ range and the detector characteristics, such as its size and the gas pressure. In this work, a study has been done in order to quantify the wall effect for the SPC, for any application. We used neutron beams, which cover the total volume of the sphere and interact with the gas nuclei, giving several reactions. The presented data derive from simulations on GEANT4 and are in agreement with the experimental data from neutron beams of the TANDEM Accelerator Laboratory, NCSR Demokritos.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| 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".