Dark matter sensitivities of the Majorana Demonstrator
Bibliographic record
Abstract
The Majorana Demonstrator is an array of natural and enriched high purity germanium detectors that will search for the neutrinoless double-beta decay of Germanium-76 and perform a search for weakly interacting massive particles with masses below 10 GeV. To reach the background rate goal in the neutrinoless double-beta decay region of interest of 4 counts/keV/t/y, the DEMONSTRATOR will utilize a number of background reduction strategies, including a time-correlated event cut for 68Ge that requires a sub-keV energy threshold. This low energy threshold allows the DEMONSTRATOR to extend its physics reach to include a search for light WIMPs. We will discuss the detector systems and data analysis techniques required to achieve sub-keV thresholds as well as present the projected dark matter sensitivities of the Majorana Demonstrator.
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How this classification was reachedexpand
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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".