Optimization of spherical proportional counter backgrounds and response for low mass dark matter search
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The NEWS-G collaboration uses Spherical Proportional Counters to search for Weakly Interacting Massive Particles (WIMP). The first detector developed for this goal is a 60 cm diameter sphere installed at the Laboratoire Souterrain de Modane in France. In 2015, the collaboration took a run with neon as the target material for an exposure of 9.7 $\\mathrm{kg\\cdot days}$. This run allowed new limits to be set on the spin-independent WIMP-nucleon cross-sections with $\\mathrm{90\\%}$ confidence upper limit of $\\mathrm{\\sigma_{SI} < 4.4 \\times 10^{-37} cm^{2}}$ for a $\\mathrm{0.5\\, GeV/c^{2}}$ WIMP. The study of the background events observed during this run shows that it is dominated by the presence of the $\\mathrm{^{210}Pb}$ decay chain in the different materials composing the detector, its shielding, and on the inner surface of the sphere. The experiences acquired during the utilization of SEDINE and the analysis of its data allowed a procedure to be developed to avoid radioactive contaminations and minimize the background of the experiment. The background of the next detector was estimated by a stringent selection of the materials, the measurements of their radioactive contaminations and the simulation of the different components. The development of new sensors allows a better homogeneity of the detector response and good data acquisition in large detector. The new detector is a 140 cm diameter sphere, to be installed at SNOLAB in Canada in 2020. Its performance will be also enhanced by the development of methods of signal characterisation and calibration.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 it