Photon asymmetry measurement in radiative muon capture on<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:msup><mml:mrow/><mml:mrow><mml:mn>40</mml:mn></mml:mrow></mml:msup></mml:mrow><mml:mi mathvariant="normal">Ca</mml:mi></mml:math>
Bibliographic record
Abstract
A measurement of the photon asymmetry $({\ensuremath{\alpha}}_{\ensuremath{\gamma}})$ in radiative muon capture RMC on ${}^{40}\mathrm{Ca}$ has been carried out at TRIUMF. Negative muons were stopped in a ${}^{40}\mathrm{Ca}$ target and the resulting RMC photons were then converted by a 5-cm thick NaI detector placed immediately in front of our main NaI detector, a cylindrical crystal of diameter 46 cm and depth 51 cm. The data sample consisted of 5200 high-energy $(57\mathrm{MeV}<{E}_{\ensuremath{\gamma}}<95\mathrm{MeV})$ RMC photon candidates. Our measured value for the energy-averaged photon asymmetry is ${\ensuremath{\alpha}}_{\ensuremath{\gamma}}=1.00\ifmmode\pm\else\textpm\fi{}0.23.$ The extracted values for the induced pseudoscalar coupling constant ${(g}_{P})$ based on this photon asymmetry measurement are ${g}_{P}{/g}_{A}<8.0,$ utilizing the impulse approximation IA model, and ${g}_{P}{/g}_{A}<14.5$ in terms of the modified impulse approximation (MIA) model. The two extracted values, although both consistent with the Goldberger-Treiman value of ${g}_{P}{/g}_{A}\ensuremath{\approx}7,$ are considerably different, indicating a significant theoretical model dependency.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".