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Record W1895969116 · doi:10.1002/andp.201300058

Laser spectroscopy of muonic hydrogen

2013· article· en· W1895969116 on OpenAlexaff
Randolf Pohl, Aldo Antognini, F. D. Amaro, F. Biraben, J. M. R. Cardoso, D. S. Covita, A. Dax, S. Dhawan, Marc Diepold, L. M. P. Fernandes, Adolf Giesen, Andrea L. Gouvea, Thomas Graf, T. W. Hänsch, P. Indelicato, L. Julién, Cheng-Yang Kao, Paul Knowles, J. A. M. Lopes, Éric-Olivier Le Bigot, Yiwei Liu, L. Ludhová, C. M. B. Monteiro, F. Mulhauser, Tobias Nebel, F. Nez, Paul Rabinowitz, J.M.F. dos Santos, L. A. Schaller, Karsten Schuhmann, Catherine Schwob, D. Taqqu, J.F.C.A. Veloso, Jan Vogelsang, F. Kottmann

Bibliographic record

VenueAnnalen der Physik · 2013
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAtomic and Molecular Physics
Canadian institutionsInstitute of Particle Physics
Fundersnot available
KeywordsCharge radiusHyperfine structureLamb shiftExotic atomSpectroscopyAtomic physicsProtonRADIUSHydrogenPhysicsLaserNuclear physicsOpticsElectronQuantum mechanics

Abstract

fetched live from OpenAlex

Muonic hydrogen (μp) is a very sensitive probe of the proton structure. Laser spectroscopy of two 2S‐2P transitions in μp was used to determine both the Lamb shift and the hyperfine splitting of the 2S state in μp. The rms charge radius of the proton, fm, was extracted from the Lamb shift. The Zemach radius of the proton, fm, was obtained from the 2S‐hyperfine splitting. This article summarizes the previously published findings.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.006
GPT teacher head0.223
Teacher spread0.217 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2013
Admission routes1
Has abstractyes

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