Bibliographic record
Abstract
Abstract nEXO is a future 5-tonne scale liquid xenon time projection chamber (TPC) experiment looking for hypothetical neutrinoless double beta decay of isotope136Xe. To attain the projected half-life sensitivity of 1028years, it aims to achieve an energy resolution of 1% or better at the Q-value (Qββ = 2.458 MeV) of the decay. nEXO plans to employ silicon photomultipliers (SiPMs) on the lateral surface of the cylindrical TPC to detect the light signals. Newly developed SiPMs sensitive to vacuum ultraviolet (VUV) light will be directly used for the detection of scintillation photons (λ = 175nm) in liquid xenon. For achieving the target energy resolution, the light detection system must have high photon detection efficiency, low correlated avalanche noise and low dark noise rate. The SiPM devices from two vendors are considered for the light detection system in the experiment. The primary goal of this research project is to characterize the VUV-SiPMs and measure their various features like gain, crosstalk, afterpulsing, dark noise rate, reflectivity and photon detection efficiency. Along with all these measurements, a monitoring tool will be required to test the large number of SiPMs before installing them in the detector. Current-voltage(IV) curve characterisation is being explored as a quick quality-testing tool for the performance of SiPM.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.056 | 0.016 |
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".