Important Factors for the Hearing Loss Caused by the Triple Semicircular Canal Occlusion in Guinea Pigs
Bibliographic record
Abstract
HYPOTHESIS: Dynamic recording of the auditory brainstem response is helpful in verifying harmful procedure(s) to hearing during triple semicircular canal occlusion (TSCO) surgery. The damage to the membranous semicircular labyrinth is the single major contributor to hearing loss caused by TSCO. BACKGROUND: Posterior semicircular canal occlusion has been recognized as an efficient method of eliminating vertigo without causing a significant hearing impairment. Recently, TSCO has also been explored for its potential to treat vertigo of various causes. In limited animal studies, varied hearing impairments have been documented after TSCO. However, the major factor(s) causing hearing loss in TSCO is/are unclear. METHODS: Triple semicircular canal occlusion was performed on 36 guinea pigs in total. The cochlear function of the guinea pigs was monitored by observing the auditory brainstem response. The impact of membranous labyrinth damage on hearing was verified by a between-group comparison. RESULTS: Hearing loss during TSCO was accumulated in every step of semicircular canal manipulation. Generally, perilymph leak was found to cause a slight hearing loss that was predominately recovered during surgery. However, transaction of the membranous labyrinth usually caused a more significant hearing loss that was not recovered during the surgery. In addition, the magnitude of hearing loss seemed to be increased with the elongation of the surgery. However, the hearing can be largely recovered after the surgery even in animals with transaction of the membranous labyrinth. CONCLUSION: Hearing loss caused by TSCO can be greatly reduced by avoiding damage to the membranous labyrinth and by shortening the operation time.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".