Combining Cochlear Analysis and Auditory Evoked Potentials in a Beluga Whale With High-Frequency Hearing Loss
Bibliographic record
Abstract
Correlations between inner ear morphology and auditory sensitivity in the same individual are extremely difficult to obtain for stranded cetaceans. Animals in captivity and rehabilitation offer the opportunity to combine several techniques to study the auditory system and cases of hearing impairment in a controlled environment. Morphologic and auditory findings from two beluga whales (Delphinapterus leucas) in managed care are presented. Cochlear analysis of a 21-year-old beluga whale showed bilateral high-frequency hearing loss. Specifically, scanning electron microscopy of the left ear revealed sensory cell death in the first 4.9 mm of the base of the cochlea with scar formation. Immunofluorescence microscopy of the right ear confirmed the absence of hair cells and type I afferent innervation in the first 6.6 mm of the base of the cochlea, most likely due to an ischemia. Auditory evoked potentials (AEPs) measured 1.5 years prior this beluga’s death showed a generalized hearing loss, being more pronounced in the high frequencies. This individual might have had a mixed hearing loss that would explain the generalized hearing impairment. Conversely, based on AEP evaluation, her mother had normal hearing and subsequent cochlear analysis did not feature any apparent sensorineural epithelium pathology. This is believed to be the first study to compare two cochlear analysis techniques and hearing sensitivity measurements from AEPs in cetaceans. The ability to combine morphological and auditory data is crucial to validate predictions of cochlear frequency maps based on morphological features. In addition, our study shows that these three complementary analysis techniques lead to comparable results, thus improving our understanding of how hearing impairment can be detected in stranding cases.
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How this classification was reachedexpand
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 | 0.000 |
| Bibliometrics | 0.000 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".