Orka, The Golden Kaon Experiment: Precision Measurement of K\rightarrow pi nu nubar and Other Ultra-Rare Processes
Bibliographic record
Abstract
ORKA is a proposed experiment to measure the K + → π + ν ν branching ratio with 5% precision using the Fermilab Main Injector high-intensity proton source.The detector design is based on the BNL E787/E949 experiments, which detected seven K + → π + ν ν candidate events.ORKA is expected to acheive two orders of magnitude improvement in sensitivity relative to the BNL experiments as a result of enhancements to the beam line and the detector acceptance.Precise measurement of the K + → π + ν ν branching ratio with the same level of uncertainty as the wellunderstood Standard Model prediction allows for sensitivity to new physics at and beyond the LHC mass scale.Detector R&D, simulation-based optimization of the experiment design, and preparation of the experiment location are underway.
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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 | 0.006 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.003 | 0.007 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".