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Record W1779633384 · doi:10.1103/physrevc.74.025809

Radiative neutron capture on a proton at big-bang nucleosynthesis energies

2006· article· en· W1779633384 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePhysical Review C · 2006
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNuclear physics research studies
Canadian institutionsTRIUMF
Fundersnot available
KeywordsPhysicsRadiative transferProtonBig Bang nucleosynthesisNeutronAmplitudeNuclear physicsEnergy (signal processing)NucleosynthesisAtomic physicsParticle physicsNuclear reactionQuantum mechanics

Abstract

fetched live from OpenAlex

The total cross section for radiative neutron capture on a proton, $\mathit{np}\ensuremath{\rightarrow}d\ensuremath{\gamma}$, is evaluated at big-bang nucleosynthesis (BBN) energies. The electromagnetic transition amplitudes are calculated up to next-to-leading-order within the framework of pionless effective field theory with dibaryon fields. We also calculate the $d\ensuremath{\gamma}\ensuremath{\rightarrow}\mathit{np}$ cross section and the photon analyzing power for the $d\stackrel{\ensuremath{\rightarrow}}{\ensuremath{\gamma}}\ensuremath{\rightarrow}\mathit{np}$ process from the amplitudes. The values of low-energy constants that appear in the amplitudes are estimated by a Markov Chain Monte Carlo analysis using the relevant low-energy experimental data. Our result agrees well with those of other theoretical calculations except for the $\mathit{np}\ensuremath{\rightarrow}d\ensuremath{\gamma}$ cross section at some energies estimated by an $R$-matrix analysis. We also study the uncertainties in our estimation of the $\mathit{np}\ensuremath{\rightarrow}d\ensuremath{\gamma}$ cross section at relevant BBN energies and find that the estimated cross section is reliable to within $~1$% error.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.715
Threshold uncertainty score0.925

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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.

Opus teacher head0.016
GPT teacher head0.299
Teacher spread0.283 · 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