APPLICATION OF THE SPH EQUIVALENCE TECHNIQUE TO THE CABRI FULL CORE IN NON-FUNDAMENTAL MODE
Bibliographic record
Abstract
We developed a SPH equivalence technique in non-fundamental mode condition between a CABRI full-core model solved with the method of characteristics (MOC) in 2D and a simplified full-core model solved with the simplified P3 (SP3) method, linear anisotropic sources and discretized with Raviart-Thomas finite elements over a pure Cartesian mesh. The MOC and SP3 calculations are performed with DRAGON5 and DONJON5 codes, respectively. A three-parameter database is generated by DRAGON5 and is interpolated in DONJON5 as a function of the core condition. An objective function is set as the root mean square (RMS) error (MOC-SP3 discrepancy) on absorption distribution and leakage rates defined over the macro-geometry in DONJON5. Our algorithm is a quasi-Newtonian gradient search based on the Limited memory Broyden-Fletcher-Goldfarb-Shanno (LBFGS) method. Numerical results are presented with Hafnium bars withdrawn or inserted.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".