Precision measurements of 20Na, 24Al, 28P, 32Cl, and 36K for the rp-process
Bibliographic record
Abstract
Explosive hydrogen burning is expected to occur in classical novae and type I x-ray bursts at temperatures up to 2 GK.Energy generation and nucleosynthesis in these events depend on the thermonuclear rates of radiative proton capture reactions involving unstable reactants.For example, the 19 Ne(p, γ) 20 Na, 23 Mg(p, γ) 24 Al, 27 Si(p, γ) 28 P, 31 S(p, γ) 32 Cl, and 35 Ar(p, γ) 36 K reaction rates are each expected to be dominated by one or two narrow, isolated resonances whose properties must be determined experimentally.First and foremost, the resonance energies must be known in order to approximate their contributions to the reaction rate and facilitate direct measurements with radioactive ion beams.By preparing thin ion implanted carbon foil targets at the University of Washington and measuring the 20 Ne( 3 He,t) 20 Na, 24 Mg( 3 He,t) 24 Al, 28 Si( 3 He,t) 28 P, 32 S( 3 He,t) 32 Cl, and 36 Ar( 3 He,t) 36 K reactions on them at 32 MeV with the Munich Q3D spectrograph, we have measured the ground state masses of 20 Na, 24 Al, 28 P, and 32 Cl and excitation energies in 32 Cl and 36 K to precisions on the order of 1 keV.We discuss our improvements on the thermonuclear rates of the 23 Mg(p, γ) 24 Al and 35 Ar(p, γ) 36 K reactions.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".