Performance of the Pacific Ocean Neutrino Experiment (P-ONE)
Bibliographic record
Abstract
The Pacific Ocean Neutrino Experiment (P-ONE) is a proposed undersea neutrino detector in the northern Pacific near the British Columbia-Washington maritime boundary, with pathfinder instrumentation already deployed. P-ONE will consist of 1400 digital optical modules distributed across 70 strings. By deploying in a deep-sea environment, the scattering of Cherenkov photons is reduced relative to experiments in glacial ice, allowing event resolutions at or below a tenth of a degree. In this poster, we present and evaluate using Monte Carlo simulations a track reconstruction method that is based on a maximum likelihood method. Recorded light pulses are evaluated using pre-computed arrival time distributions of Cherenkov photons at optical modules as functions of track parameters. The corresponding angular resolution of the detector, when combined with the anticipated neutrino effective area, can be used to estimate the discovery potential, the flux needed to discover a point source of astrophysical neutrinos with P-ONE.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".