Revisiting Elastic Scattering of D(n, n)D reaction
Bibliographic record
Abstract
Interest has risen recently concerning the angular distribution of neutron elastic scattering on deuterium at low incident energies. The main subject is the amount of backscatter at energies below 3.2 MeV observed in differential cross‐section measurements and represented in various evaluations. These various angles of approach encompass fundamental nuclear‐data measurements, three‐body nuclear‐theory calculations, evaluated nuclear ‐data libraries and associated data processing, and the simulation of critical experiments involving heav y water. A new theoretical approach on the basis of three ‐nucleon theory was made that resulte d in new angular distributions. At the GELINA neutron time‐of‐flight facility a new experimental setup was developed to measure elastic scattering of neutrons on deuterium in the energy range of interest. The technique proposed is complementary to the earlier works by detecting the scattered neutron instead of the recoiling deuterium. The setup is an array of two HPGe detectors, each with a 10B neutron‐gamma converter. Preliminary GELINA findings using a C6D6 target indicate less backscatter than predicted by ENDF/B ‐VII.0, in contrast to the nuclear‐theory results. It is expected that completion of the planned work will reduce the uncertainty of the energy‐angle distributions for deuterium elastic scattering and contribute to an improved deuterium evaluation in a future release of ENDF/B ‐VII.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".