A Design of Experiments Analysis to Determine the Importance of Relevant Factors on the STL of an Acoustic Part
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Bibliographic record
Abstract
<div class="section abstract"><div class="htmlview paragraph">This paper discusses a design of experiments (DOE) analysis that was performed to understand relevant factors that influence the acoustic performance of a sound package part used in the commercial vehicle industry for the floor mat application. The acoustic performance of the sound package part which is a double wall system and constructed of a barrier and cellular decoupler material is expressed in terms of sound transmission loss (STL). An experiment was designed using the Taguchi DOE technique with three factors and three levels to acquire the STL data and is discussed in the paper. The results of the DOE analysis and the confidence in the model are discussed as well as the benefits of predicting expected STL performances are mentioned in the paper.</div></div>
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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