Design of the Pacific Ocean Neutrino Experiment`s First Detector Line
Bibliographic record
Abstract
The Pacific Ocean Neutrino Experiment (P-ONE) is a planned multi-cubic-kilometer neutrino telescope in the depths of the Northeast Pacific Ocean, offshore of Vancouver Island, British Columbia. Its primary scientific objective is the detection of high-energy neutrinos, which as cosmic messengers, are crucial to complement our understanding of the origin and acceleration mechanisms of cosmic rays. P-ONE will be connected to an existing deep-sea infrastructure, the NEPTUNE observatory, hosted by Ocean Networks Canada (ONC). Following the successful deployment of two pathfinder missions, aiming for the characterization of the proposed deployment location, the P-ONE collaboration with its partners atONCisworking towards the realization of the first detector line of P-ONE. The challenging deepsea environment, ocean dynamics, background variations induced by bioluminescence and 40K decay, as well as the aim for modularity and scalability, require novel approaches to the detector design. The P-ONE-1 line strives to overcome these challenges and ultimately serve as a blueprint for the following installations. P-ONE-1 will comprise 20 optical and calibration modules, enclosed in glass hemispheres and integrated with a novel hybrid cable architecture with a combined length of just over 1000 m.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.008 |
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".