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Record W3186145344 · doi:10.48550/arxiv.2107.11462

LEGEND-1000 Preconceptual Design Report

2021· preprint· en· W3186145344 on OpenAlex

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenuearXiv (Cornell University) · 2021
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicColor Science and Applications
Canadian institutionsnot available
FundersScience and Technology Facilities Council
KeywordsLegendMedicineEngineeringHistoryArt history

Abstract

fetched live from OpenAlex

Parallel talk presented at the XXI International Workshop on Neutrino Telescopes - Padova 29 September - 3 October 2025 (https://agenda.infn.it/event/44606/) On behalf of the LEGEND Collaboration Abstract: The LEGEND experiment searches for the neutrinoless double-beta (0νββ) decay of Ge-76 using isotopically-enriched high-purity germanium (HPGe) detectors with the ultimate discovery sensitivity beyond a half-life of 10^28 years. The project is conducted in stages. The first one, LEGEND-200, was steadily accumulating physics data at LNGS (Laboratori Nazionali del Gran Sasso, Italy) for more than one year with 140 kg of HPGe detectors. In 2024 the Collaboration unblinded the first data to check the sensitivity of the experiment and study the composition of the LEGEND-200 background, which was slightly higher than predicted based on screening measurements of the components. The detector array was subsequently disassembled to investigate the source of the elevated background, with nearby components undergoing re-cleaning and/or replacement as necessary. LEGEND-200 is scheduled to resume data taking in 2025. In this talk we will present the performance of the ongoing experiment and give an update on the status of its second phase: LEGEND-1000. Funds: This work is supported by the U.S. DOE and the NSF, the LANL, ORNL and LBNL LDRD programs; the European ERC and Horizon programs; the German DFG, BMBF, and MPG; the Italian INFN; the Polish NCN and MNiSW; the Czech MEYS; the Slovak RDA; the Swiss SNF; the UK STFC; the Canadian NSERC and CFI; the LNGS and SURF facilities.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.697
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.106
GPT teacher head0.208
Teacher spread0.102 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it