Recent results from the MAJORANA DEMONSTRATOR
Bibliographic record
Abstract
The MAJORANA DEMONSTRATOR is an experiment constructed to search for neutrinoless double-beta decay in $^{76}$Ge and to demonstrate the feasibility to deploy a large-scale experiment in a phased and modular fashion. It consists of two modules of natural and $^{76}$Ge-enriched germanium detectors totalling $44.1\ \mathrm{kg}$, operating at the 4850' level of the Sanford Underground Research Facility in Lead, South Dakota, USA. Commissioning of the experiment began in June 2015, followed by data production with the full detector array in August 2016. The ultra-low background and record energy resolution achieved by the MAJORANA DEMONSTRATOR enable a sensitive neutrinoless double-beta decay search, as well as additional searches for physics beyond the Standard Model. I will discuss the design elements that enable these searches, along with the latest results, focusing on the neutrinoless double-beta decay search. I will also discuss the current status and the future plans of the MAJORANA DEMONSTRATOR, as well as the plans for a future tonne-scale $^{76}$Ge experiment.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.006 |
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".