Distinguishing Healthy from Otosclerotic Ears: Effect of Probe-Tone Frequency on Static Immittance
Bibliographic record
Abstract
The diagnostic utility of static immittance (SI) with respect to distinguishing healthy from otosclerotic ears was investigated at different probe-tone frequencies in 68 healthy ears and 36 ears with surgically confirmed otosclerosis. Because one effect of otosclerosis is to shift the resonant frequency of the middle ear to higher values as a result of increased stiffness of the middle ear system, it was hypothesized that SI measured at higher probe-tone frequencies may provide a better distinction between healthy and otosclerotic ears. As expected, the results of this study indicate that SI measured at higher probe-tone frequencies is superior to a standard low probe tone in the detection of otosclerotic ears. Through systematic and objective comparisons of relevant probetone frequencies using both group statistics and test performance analysis, the present study suggests 630 Hz as an optimum probe-tone frequency for measuring SI with respect to distinguishing healthy ears from otosclerotic ears.
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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 | 0.002 | 0.018 |
| 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 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".