Mass Chain Evaluations for the Evaluated Nuclear Structure Data File (ENSDF)—An Urgent Appeal for European Participation
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.
Bibliographic record
Abstract
Abstract Reliable nuclear structure and decay data represent the fundamental building blocks of nuclear physics and astrophysics research, and are also of vital importance in a significant number of applied nuclear fields such as power generation and associated fuel cycle operations (e.g., fuel manufacture, transport, reprocessing, and waste management), materials analysis, medical diagnosis, and radiotherapy. There is a continuous demand for good quality data formulated and recommended through the speedy assessment and incorporation of new and improved measurements. Acknowledgements The authors express their gratitude to all colleagues within the International Network of Nuclear Structure and Decay Data Evaluators for their enthusiastic efforts to maintain the quality of the existing nuclear structure databases. F. G. Kondev and J. K. Tuli are supported by the U.S. Department of Energy, Office of Nuclear Physics, Office of Science, under contracts DE-AC02-06CH11357 and DE-AC02-98CH10886, respectively. Notes 9. H. D. Choi, R. B. Firestone, R. M. Lindstrom, G. L. Molnár, S. F. Mughabghab, R. Paviotti-Corcuera, Z. Révay, A. Trkov, V. Zerkin, and C. Zhou, Database of prompt gamma rays from slow neutron capture for elemental analysis, STI/PUB/1263, International Atomic Energy Agency, Vienna, Austria (2007), ISBN 92-0-101306-X.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it