Fundamental Symmetries, Neutrons, and Neutrinos (FSNN): Whitepaper for the 2023 NSAC Long Range Plan
Bibliographic record
Abstract
II. Introduction & scientific questions driving the field III.Progress since the last Long Range Plan A. Searches for neutrinoless double beta decay B. Searches for electric dipole moments C. Parity-violating electron scattering D. Precision beta decay with nuclei E. Precision beta decay with neutrons F. Precision Measurements with muons and mesons G. Hadronic Parity and Time-Reversal Violation H. Searches for neutron oscillations I. Neutrino mass and sterile neutrinos J. Neutrino interactions K. Neutrinos in astrophysics and cosmology L. Other precision measurements IV.Synopsis of current and future projects V. Recommendation I: Lepton Number Violation and Neutrinoless Double Beta Decay A. Significance of Research B. Relationship with other probes of neutrino mass and lepton number violation C. Introduction to 0νβ β experiments D. Ton-scale experimental program E. Beyond ton-scale F. Summary VI.Recommendation II: Targeted Program A. CP-violation: Electric Dipole Moments and other observables 1. Significance of Research 2. Neutron EDM experiments 3. Atomic and molecular EDM experiments B. Precision tests of the Standard Model as probes of new physics 1. Parity Violating Electron Scattering 2. Precision beta decays Nuclear Decays Neutron Decays 3. Precision muon and meson experiments 4. Hadronic Parity and Time-Reversal Violation 5. Baryon Number Violation: neutron oscillations C. Properties of neutrinos and hypothetical light particles 1. Absolute neutrino mass measurements and sterile neutrinos 2. Neutrino scattering
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.073 | 0.045 |
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".