Bibliographic record
Abstract
CONCLUSION: Cochlear microphonic (CM) measurements may potentially become a supplementary approach to otoacoustic emission (OAE) measurements for assessing low-frequency cochlear functions in the clinic. OBJECTIVE: The objective of this study was to investigate the measurement of CMs in subjects with high-frequency hearing loss. Currently, CMs can be measured using electrocochleography (ECochG or ECoG) techniques. Both CMs and OAEs are cochlear responses, while auditory brainstem responses (ABRs) are not. However, there are inherent limitations associated with OAE measurements such as acoustic noise, which can conceal low-frequency OAEs measured in the clinic. However, CM measurements may not have these limitations. METHODS: CMs were measured in human subjects using an ear canal electrode. The CMs were compared between the high-frequency hearing loss group and the normal-hearing control group. Distortion product OAEs (DPOAEs) and audiogram were also measured. RESULTS: The DPOAE and audiogram measurements indicate that the subjects were correctly selected for the two groups. Low-frequency CM waveforms (CMWs) can be measured using ear canal electrodes in high-frequency hearing loss subjects. The difference in amplitudes of CMWs between the high-frequency hearing loss group and the normal-hearing group is insignificant at low frequencies but significant at high frequencies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".