SuperCDMS Underground Detector Fabrication Facility
Bibliographic record
Abstract
The SuperCDMS SNOLAB dark matter experiment processes Ge and Si crystals into fully tested phonon and ionization detectors at surface fabrication and test facilities. If not mitigated, it is anticipated that trace-level production of radioisotopes in the crystals due to exposure to cosmic rays at (or above) sea level will result in the dominant source of background events in future dark matter searches using the current SuperCDMS detector technology. Fabrication and testing of detectors in underground facilities shielded from cosmic radiation is one way to directly reduce production of trace levels of radioisotopes, thereby improving experimental sensitivity for the discovery of dark matter beyond the level of the current experiment. In this report, we investigate the cost and feasibility to establish a complete detector fabrication processing chain in an underground location to mitigate cosmogenic activation of the Ge and Si detector substrates. For a specific and concrete evaluation, we explore options for such a facility located at SNOLAB, an underground laboratory in Sudbury, Canada hosting the current and future experimental phases of SuperCDMS.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.033 | 0.011 |
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".