Bibliographic record
Abstract
Abstract The Jiangmen Underground Neutrino Observatory (JUNO) is a 20 kton multi-purpose liquid scintillator detector with an expected 3 % / E [ Mev ] energy resolution, under construction in a 700 m underground laboratory in the south of China (Jiangmen city, Guangdong province). The exceptional energy resolution and the massive fiducial volume of the JUNO detector offer great opportunities for addressing many essential topics in neutrino and astroparticle physics. JUNO’s primary goals are to determine the neutrino mass ordering and precisely measure the related neutrino oscillation parameters. With six years of data taking with reactor antineutrinos, JUNO can determine the mass ordering at a 3-4σ significance and the neutrino oscillation parameters sin2 θ 12, Δ m 21 2 , and | Δ m 31 2 | to a precision of better than 0.6%. In addition, the atmospheric neutrino and solar neutrino measurement at JUNO can also provide complementary and important information for neutrino oscillation physics. This work focuses on the oscillation physics of JUNO, which includes measurement and analysis of the reactor neutrinos, the atmospheric neutrinos, and the solar neutrinos. With the delicate energy response calibration and event reconstruction potential, JUNO will make a world-leading measurement on the neutrino oscillation parameters and neutrino mass ordering in the near future.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.022 | 0.003 |
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".