Numerical cost of gradient computation within the method of moments and its reduction by means of a novel boundary-layer concept
Why this work is in the frame
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Bibliographic record
Abstract
A rigorous investigation of the numerical cost of sensitivity analysis (gradient computation) of complex structures within moment method is presented. It is shown that, when the number of variables N used in the analysis is large, a common situation in complex structures, the ratio r of the number of flops required to evaluate the sensitivity of the response to structural changes to the number of flops required to determine the response at a single point is such that r=0(1/N) as long as the number of flops required to fill the matrix is not dominant. For the latter important case, a new boundary layer concept is introduced to reduce the CPU time for the gradient computation. A simple example of an iris in a rectangular waveguide is used to illustrate the concept and show its validity.
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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 | 0.000 |
| 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