Databases and tools for nuclear astrophysics applications
Bibliographic record
Abstract
An update of a previous description of the BRUSLIB + NACRE package of nuclear data for astrophysics and of the web-based nuclear network generator NETGEN is presented. The new version of BRUSLIB contains the latest predictions of a wide variety of nuclear data based on the most recent version of the Brussels-Montreal Skyrme-Hartree-Fock-Bogoliubov model. The nuclear masses, radii, spin/parities, deformations, single-particle schemes, matter densities, nuclear level densities, E1 strength functions, fission properties, and partition functions are provided for all nuclei lying between the proton and neutron drip lines over the 8 ≤ Z ≤ 110 range, whose evaluation is based on a unique microscopic model that ensures a good compromise between accuracy, reliability, and feasibility. In addition, these various ingredients are used to calculate about 100 000 Hauser-Feshbach neutron-, proton-, α-, and γ-induced reaction rates based on the reaction code TALYS. NACRE is superseded by the NACRE II compilation for 15 charged-particle transfer reactions and 19 charged-particle radiative captures on stable targets with mass numbers A < 16. NACRE II features the inclusion of experimental data made available after the publication of NACRE in 1999 and up to 2011. In addition, the extrapolation of the available data to the very low energies of astrophysical relevance is improved through the systematic use of phenomenological potential models. Uncertainties in the rates are also evaluated on this basis. Finally, the latest release v10.0 of the web-based tool NETGEN is presented. In addition to the data already used in the previous NETGEN package, it contains in a fully documented form the new BRUSLIB and NACRE II data, as well as new experiment-based radiative neutron capture cross sections. The full new versions of BRUSLIB, NACRE II, and NETGEN are available electronically from the nuclear database at http://www.astro.ulb.ac.be/NuclearData. The nuclear material is presented in an extended tabular form complemented with a variety of graphical interfaces.
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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 | 0.005 | 0.022 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.010 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.009 | 0.010 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.106 | 0.157 |
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".