A Sequential Iterative Scheme for Design of Experiments in Complex Polymerizations
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Bibliographic record
Abstract
Abstract The Bayesian design approach is an experimental design technique which has many advantages over standard experimental designs. It incorporates prior knowledge about the process into the design to suggest a set of future experiments in an optimal, sequential, and iterative fashion. Since for many complex polymerizations prior information is available, either in the form of experimental data or mathematical models, the use of Bayesian design methodology could be beneficial. Exploiting this technique in complex polymerizations could hopefully lead to optimal performance in fewer trials, thus saving time and money. Advantages of the Bayesian design approach are illustrated via case studies drawn from the nitroxide‐mediated radical polymerization as an example. However, since this technique is perfectly general, it can be potentially applied to other polymerization variants.
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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