Development of a Reference Database for Beta-Delayed Neutron Emission
Bibliographic record
Abstract
Beta-delayed neutron emission is important for nuclear structure and astrophysics as well as for reactor applications. Significant advances in nuclear experimental techniques in the past two decades have led to a wealth of new measurements that remain to be incorporated in the databases. We report on a coordinated effort to compile and evaluate all the available beta-delayed neutron emission data. The different measurement techniques have been assessed and the data have been compared with semi-microscopic and microscopic-macroscopic models. The new microscopic database has been tested against aggregate total delayed neutron yields, time-dependent group parameters in 6-and 8-group re-presentation, and aggregate delayed neutron spectra. New recommendations of macroscopic delayed-neutron data for fissile materials of interest to applications are also presented. The new Reference Database for Beta-Delayed Neutron Emission Data is available online at: http://www-nds.iaea.org/beta-delayed-neutron/database.html.
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 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 | 0.007 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.022 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.007 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 0.024 |
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".