A Monte Carlo Lattice Code with Probability Tables and Optimized Energy Meshes
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Bibliographic record
Abstract
The possibility of performing Monte Carlo transport calculations using cross-section probability tables on the entire energy spectrum is discussed in this paper. This method possesses straight advantages toward other representations: Self-shielding effects are represented during the random walk in a straightforward way, and the calculation cost remains below continuous-energy simulations. This study takes advantage of previous contributions made in subgroup-based self-shielding models, regarding the definitions of optimized energy meshes and adequate numerical methods for consistently computing cross-section probability tables. Moment-based probability-table cross sections along with an energy mesh comprising only 295 groups lead to results with a similar level of accuracy to those obtained with a continuous-energy Monte Carlo method. Another innovative aspect of this work is related to the introduction of correlated weight matrices into a Monte Carlo algorithm. These correlated weights are used to represent mutual self-shielding effects occurring where resonances of different isotopes overlap.
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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 | 0.001 |
| Open science | 0.000 | 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