<i>In vivo</i> measurement of basilar membrane vibration in the unopened chinchilla cochlea using high frequency ultrasound
Bibliographic record
Abstract
The basilar membrane and organ of Corti in the cochlea are essential for sound detection and frequency discrimination in normal hearing. There are currently no methods used for real-time high resolution clinical imaging or vibrometry of these structures. The ability to perform such imaging could aid in the diagnosis of some pathologies and advance understanding of the causes. It is demonstrated that high frequency ultrasound can be used to measure basilar membrane vibrations through the round window of chinchilla cochleas in vivo. The basic vibration characteristics of the basilar membrane agree with previous studies that used other methods, although as expected, the sensitivity of ultrasound was not as high as optical methods. At the best frequency for the recording location, the average vibration velocity amplitude was about 4 mm/s/Pa with stimulus intensity of 50 dB sound pressure level. The displacement noise floor was about 0.4 nm with 256 trial averages (5.12 ms per trial). Although vibration signals were observed, which likely originated from the organ of Corti, the spatial resolution was not adequate to resolve any of the sub-structures. Improvements to the ultrasound probe design may improve resolution and allow the responses of these different structures to be better discriminated.
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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 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".