Using Concha Electrodes to Measure Cochlear Microphonic Waveforms and Auditory Brainstem Responses
Bibliographic record
Abstract
During electrocochleography, that is, ECochG or ECoG, a recording electrode can be placed in the ear canal lateral to the tympanic membrane. We designed a concha electrode to record both sinusoidal waveforms of cochlear microphonics (CMs) and auditory brainstem responses (ABRs). The amplitudes of CM waveforms and Wave I or compound action potentials (CAPs) recorded at the concha were greater than those recorded at the mastoid but slightly lower than those recorded at the ear canal. Wave V amplitudes recorded at the concha were greater than those recorded at the ear canal but lower than those recorded at the mastoid. There was not a significant difference between the amplitudes recorded at the concha and at the ear canal. For CM and Wave I or CAP, the latency recorded at the concha was longer than at the canal but shorter than at the mastoid; for Wave V, the reverse was true. However, these differences were not statistically significant and may be due to the distance to response generators. Aside from the advantages that the regular ECoG has over otoacoustic emission (OAE) testing, the concha electrode was also easier and safer to place and may be suitable for children, newborn screening, participants with canal conditions, and remote clinics which could have concerns with the availability and cost of a canal electrode. Using concha electrodes, we also experienced fewer postauricular artifacts than when using a mastoid electrode.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".