Development and testing of the optical module for the Pacific Ocean Neutrino Experiment (P-ONE)
Bibliographic record
Abstract
The P-ONE (Pacific Ocean Neutrino Experiment) is a future cubic-km-scale, water Cherenkov neutrino telescope that will be located in the Pacific Ocean off the coast of Canada. This telescope will contribute to the search for astrophysical neutrino sources, test improved detection and calibration techniques, and provide valuable oceanographic measurements. The first line of the detector, named P-ONE-1, is currently under production.The first line of the detector, named P-ONE-1, is currently in production. The P-ONE Optical Module (P-OM) consists of sixteen 3-inch photomultiplier tubes (PMTs), as well as a series of calibration devices (flashers, acoustic devices, axicons and muon scintillators), which will be used to characterise the optical properties of water and measure the initial performance of the line. The PMT waveforms are digitzed by a 16-channel (210 MHz) analog-to-digital converter (ADC) with a timing system providing an estimated accuracy of 0.1 ns. After assembling the P-OM, it will be essential to characterise and calibrate the different photosensors in order to create an accurate simulation of the mooring line and verify that the modules function properly. Therefore, at the Technical University of Munich a dedicated automatic calibration setup consisting of multiple light sources and a rotation stage was developped to perform quality control of the P-OM hemispheres and measure the properties of the PMTs. This contribution will discuss the different feature and subsystem of the optical module and its measured performance.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.003 | 0.001 |
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".