Measurement of CP Asymmetry in B0 to Ks pi0 pi0 Decays
Bibliographic record
Abstract
We present a measurement of the time-dependent CP asymmetry for the neutral B-meson decay into the CP = +1 final state Ks pi0 pi0, with Ks -> pi+ pi-. We use a sample of approximately 227 million B-meson pairs recorded at the Upsilon(4S) resonance with the BABAR detector at the PEP-II B-Factory at SLAC. From an unbinned maximum likelihood fit we extract the mixing-induced CP-violation parameter S = 0.72 +/- 0.71 +/- 0.08 and the direct CP-violation parameter C = 0.23 +/- 0.52 +/- 0.13, where the first uncertainty is statistical and the second systematic.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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 teacher head, 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".