The Under-Water Dark-Room Experimental Facility at the University of Winnipeg
Bibliographic record
Abstract
A completely new under-water dark-room test facility (UWDTF) has been built at the University of Winnipeg during 2021-2023, for the testing of the equipments, optical components and detectors before they might be used in different underwater experiments, like the Hyper-Kamiokande (Hyper-K), and others. The Facility is designed for Research and Development activities primarily related to the different calibration systems, which are/will be used in the Water Cherenkov Test Experiment (WCTE) at CERN, the Intermediate Water Cherenkov Detector (IWCD) at Tokai, Japan and the Hyper-Kamiokande Far Detector at Kamioka, Japan. The facility houses a large tank of water (1000 gallons) in an optically isolated room, and is equipped with a gantry that provides for the 3D motion of a maximum of 50 lbs of load inside the tank. A customized pan-tilt system has also been devised to accommodate further degrees of freedom of motion to the payload in the polar and azimuthal direction. The facility is primarily used for testing of the under-water camera housings designed for the Hyper-K experiment, besides many other research and development activities. The preliminary results of the camera calibration done in this multi-purpose underwater-darkroom facility are presented here, starting with the description of the vital features of this facility.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".