Middle ear of human and pig: a comparison of structures and mechanics
Bibliographic record
Abstract
INTRODUCTION: Animal studies are an essential method to evaluate implants for the middle ear prior to clinical studies. New Zealand rabbits, guinea pigs and chinchillas are, among other small mammals, well established animal models, but their auditory system is significantly smaller compared to human. Hence, the suitability of the domestic pig (sus scrofa domesticus) as a new animal model for research on the middle ear (ME), that would match the human in size, was investigated. METHODS: Thirty halved pig heads were obtained from the butcher and each middle ear was dissected. Using a digital light microscope, several anatomical magnitudes were determined for 24 specimens, namely the planar projected area of the tympanic membrane (TM), in relation to the stapes footplate as well as the dimensions and weight of the ossicles, in order to determine the effective lever ratios. Using normal and micro computed tomography (CT), six porcine temporal bones were scanned and the geometric data obtained were transferred into a finite element model (FEM) simulation of the porcine middle ear. The transfer function was determined and compared to those from humans determined by measurements and simulations, respectively. RESULTS: The anatomy investigated presented itself as highly comparable to that of the human. Differing from literature, no fourth ossicle could be found. The porcine dimensions and lever ratios determined match the humans far better than those of all established animal models. The obtained transfer function was congruent to the human one. This underlines the suitability of the pig as an animal model for middle ear implants.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".