Calibration of the PICO-0.1 bubble chamber and development of coated inner vessels for dark matter search
Bibliographic record
Abstract
The detection of dark matter is one of the biggest challenges in modern physics. The PICO experiment aims for the direct detection of Weakly Interacting Massive Particles (WIMPs) with bubble chambers. In this thesis, results from calibrations of the PICO-0.1 test chamber is presented. Calibrations were performed at the Tandem Van de Graaff facility of the Université de Montréal. Monoenergetic neutrons were produced from the 51V(p,n)51Cr reaction with a 1.6 MeV proton beam. Two 3He neutron counters used during calibrations for neutron flux normalization were also calibrated. This result is contributing in improving Monte Carlo simulations of PICO-0.1. Finally, preliminary work was done toward the use of new inner vessel materials with coated surfaces for bubble chambers. A Condensation Bubble Chambers (CBCs) was used as a test-bench. Progress has been made toward the usability of Poly-methyl-methacrylate vessels, but more work is needed to solve spontaneous wall nucleation problems.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".