Assessment of Ear Disorders Using Power Reflectance
Bibliographic record
Abstract
This article describes the effect of various pathologies on power reflectance (PR) and absorbance measured in human adults. The pathologies studied include those affecting the tympanic membrane, the middle-ear ossicles, the middle-ear cavity, the inner ear, and intracranial pressure. Interesting pathology-induced changes in PR that are statistically significant have been reported. Nevertheless, because measurements of PR obtained from normal-hearing subjects have large variations and some pathology-induced changes are small, it can be difficult to use PR alone for differential diagnosis. There are, however, common clinical situations without reliable diagnostic methods that can benefit from PR measurements. These conditions include ears with a normal-appearing tympanic membrane, aerated middle-ear cavity, and unknown etiology of conductive hearing loss. PR measurements in conjunction with audiometric measurements of air–bone gap have promise in differentiating among stapes fixation, ossicular discontinuity, and superior semicircular canal dehiscence. Another possible application is to monitor an individual for possible changes in intracranial pressure. Descriptions of mechanisms affecting PR change and utilization of PR measurements in clinical scenarios are presented.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".