The Scintillation Bubble Chamber (SBC) experiment for dark matter and reactor CEvNS
Bibliographic record
Abstract
The Scintillating Bubble Chamber (SBC) Collaboration is developing a novel detection technique aimed at detecting low-mass (0.7-7 GeV/c$^2$) WIMP interactions and coherent elastic neutrino-nucleus scattering (CE$\nu$NS) of reactor neutrinos. Using a target volume composed of super-heated argon with a tiny amount of dissolved xenon, the nucleation signal from electron recoils (the limiting factor for low-threshold studies in bubble chambers) is suppressed, allowing for the exploration of new parameter space. Particle interactions with the target fluid can lead to the production of heat (bubbles) and scintillation light. By combining these observables, the SBC Collaboration is aiming to reach a threshold of 100 eV for nuclear recoil detection with discrimination and a projected WIMP-sensitivity of $1.73\times10$^{-43}\rm{cm}^2$, for a WIMP mass of 1 GeV/c$^2$. In this paper, the design of a 10-kg device and the current activities at Fermilab (FNAL) towards the commissioning and operation of the detector are presented. As part of the detector R\&D, ongoing activities at the University of Alberta for different image capture setups are also briefly discussed afterward. Finally, an overview of the collaboration’s plans for future operations at FNAL and SNOLAB, including the potential for such a detector to become the leading technology to study CE$\nu$NS are also presented here.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".