Probabilistic design of systems with general distributions of parameters
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Bibliographic record
Abstract
Abstract This paper presents a new method for finding optimal solutions of systems with design parameters which are random variables distributed with various general and possibly non‐symmetrical distributions. A double‐bounded density function is used to approximate the distributions. Specifications may require tracking constraints in time domain and stability conditions in frequency domain. Using sensitivity information, the proposed method first finds a linearized feasible region. Afterwards it attempts to place a tolerance box of the design parameters such that the region with higher yield lies in the feasible region. The yield is estimated by the joint cumulative density function over a portion of the tolerance box contained in the feasible region. Optimal designs are found for a fourth‐order servomechanism and actual yields are evaluated by Monte‐Carlo simulation. Copyright © 2001 John Wiley & Sons, Ltd.
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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 | 0.002 | 0.001 |
| 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