Hyper-Kamiokande Physics Opportunities Submitted by the Hyper-Kamiokande Working Group ∗
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.
Bibliographic record
Abstract
We propose the Hyper-Kamiokande (Hyper-K) detector as a next generation un-derground water Cherenkov detector [1]. It will serve as a far detector of a long base-line neutrino oscillation experiment envisioned for the upgraded J-PARC beam, and as a detector capable of observing, far beyond the sensitivity of the Super-Kamiokande (Super-K) detector, proton decays, atmospheric neutrinos, and neutrinos from astro-physical origins. The current baseline design of Hyper-K is based on the highly suc-cessful Super-K detector, taking full advantage of a well-proven technology. Hyper-K consists of two cylindrical tanks lying side-by-side, the outer dimensions of each tank being 48(W) × 54(H) × 250(L) m3. The total (fiducial) mass of the detector is 0.99 (0.56) million metric tons, which is about 20 (25) times larger than that of Super-K. A proposed location for Hyper-K is about 8 km south of Super-K (and 295 km away from J-PARC) at an underground depth of 1,750 meters water equivalent (m.w.e.). The inner detector region of the Hyper-K detector is viewed by 99,000 20-inch PMTs, corresponding to the PMT density of 20 % photo-cathode coverage (one half of that of Super-K). The Hyper-K project is envisioned to be completely open to the international community. The current working group contains members from Canada, Japan,
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it