A new finite-element model of the incudostapedial joint
Bibliographic record
Abstract
Although the joints of the ossicular chain contribute significantly to sound transmission through the middle ear, the mechanical behaviour of these joints is poorly understood. We have previously presented finite-element (FE) models of the incudostapedial joint (ISJ) that were structurally based on histological serial sections and X-ray microCT scans, and that used plausible estimates for material-property parameters. Models with or without the presence of synovial fluid in the joint were made and preliminary simulations were compared with experimental tension and compression measurements. Later we presented an analytical model of the joint with a simplified geometry using the theory of large deformations of elastic membranes to model the joint capsule. Results indicated that the mechanical behaviour of the incudostapedial joint may be influenced by mechanical instabilities of the joint capsule. This was observed for forces near zero in a simulated tension-compression test and could result in a jump in the corresponding force-displacement curve. In this work, we present new finite-element simulations where we model the synovial gap with a liquid-like incompressible material and perform a sensitivity analysis to see the effect of various properties, such as capsule length, synovial-fluid volume, and joint cross-sectional shape on the mechanical behaviour of the joint. The results are compared with experimental results from the literature.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".