Audiometric findings with voluntary tensor tympani contraction
Bibliographic record
Abstract
BACKGROUND: Tensor tympani contraction may have a "signature" audiogram. This study demonstrates audiometric findings during voluntary tensor tympani contraction. METHODS: Five volunteers possessing the ability to voluntarily contract their tensor tympani muscles were identified and enrolled. Tensor tympani contraction was confirmed with characteristic tympanometry findings. Study subjects underwent conventional audiometry. Air conduction and bone conduction threshold testing was performed with and without voluntary tensor tympani contraction. MAIN OUTCOME MEASURE: Changes in air conduction and bone conduction thresholds during voluntary tensor tympani contraction. RESULTS: Audiometric results demonstrate a low frequency mixed hearing loss resulting from tensor tympani contraction. Specifically, at 250 Hz, air conduction thresholds increased by 22 dB and bone conduction thresholds increased by 10 dB. CONCLUSIONS: Previous research has demonstrated a low frequency conductive hearing loss in the setting of tensor tympanic contraction. This is the first study to demonstrate a low frequency mixed hearing loss associated with tensor tympani contraction. This finding may aid in the diagnosis of disorders resulting from abnormal tensor tympani function. Tensor tympani contraction should be included on the differential for low frequency mixed hearing loss.
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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 | 0.003 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".