Stochastic Finite Element Modelling of Human Middle-Ear
Why this work is in the frame
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Bibliographic record
Abstract
Modelling the mechanics of the middle-ear is important as it can extend our knowledge about the hearing process and enable us to develop new devices for the treatment and diagnosis of hearing disabilities. Most of the works in the literature of the modelling of middle-ear mechanics are focused on deterministic models. These models cannot consider the variability of input parameters that can happen due to the stochastic nature of the mechanical properties of tissues and variability between individuals. Stochastic models can consider the variability in the parameters and make us able to have more realistic representations of the physiology. In this work, we present a stochastic Finite Element Method (FEM) model of the human middle-ear. We considered uncertainty in all mechanical properties and some geometrical properties of the middle-ear model and studied the effects of these uncertainties on the uncertainties of the outputs of the model.
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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