The EUSO@Turlab Project: Results from Phase II
Bibliographic record
Abstract
The TurLab facility is a laboratory, equipped with a 5 m diameter and 1 m deep rotating tank,located in the Physics Department of the University of Turin. Originally built mainly to study problems where system rotation plays a key role in the fluid behaviour such as in atmospheric and oceanic flows at different scales, in the past few years the TurLab facility has been used to perform experiments related to observation of Extreme Energy Cosmic Rays from space using the fluo-rescence technique, as in the case of the JEM-EUSO mission, where the diffuse night brightness and artificial light sources can vary significantly in time and space inside the Field of View of the telescope. The description of the EUSO@TurLab project and its first results have been presented in the past. During the last two years many upgrades have been performed on the instrumenta-tion mainly related to the read-out electronics: SPACIROC-1 (employed in EUSO-Balloon and EUSO-TA prototypes) and SPACIROC-3 (EUSO-SPB and Mini-EUSO) which allowed to test a fully equipped Elementary Cell of JEM-EUSO. This phase has been named Phase II. Moreover, the Focal Surface of EUSO-Balloon with the level 1 trigger logic implemented in the Photo-Detector Module has been tested at TurLab after the Canada flight. Finally, tests related to the possibility to employ a EUSO-like detector for other type of applications such as wave monitor- ing and imaging detector have been pursued. The tests and results obtained in EUSO@TurLab Project - Phase II are described.
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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 | 0.010 | 0.005 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".