A geometrically nonlinear finite-element model of the cat eardrum
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Current finite-element (FE) models of the eardrum are limited to low pressures because of the assumption of linearity. Our objective is to investigate the effects of geometric nonlinearity in FE models of the cat eardrum with an approximately immobile malleus for pressures up to +/-2.2 kPa, which are within the range of pressures used in clinical tympanometry. Displacements computed with nonlinear models increased less than in proportion to applied pressure, similar to what is seen in measured data. In both simulations and experiments, there is a shift inferiorly in the location of maximum displacement in response to increasingly negative middle-ear pressures. Displacement patterns computed for small pressures and for large positive pressures differed from measured patterns in the position of the maximum pars-tensa displacement. Increasing the thickness of the postero-superior pars tensa in the models shifted the location of the computed maximum toward the measured location. The largest computed pars-tensa strains were mostly less than 2%, implying that a linearized material model is a reasonable approximation. Geometric nonlinearity must be considered when simulating eardrum response to high pressures because purely linear models cannot take into account the effects of changing geometry. At higher pressures, material nonlinearity may become more important.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.001 |
| 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