Peaks between peaks: Comparative intra-ear correlations in spontaneous otoacoustic emissions
Bibliographic record
Abstract
Spontaneous otoacoustic emissions (SOAEs) are a key facet of modern models of inner ear biomechanics, as the phenomenon provides crucial insight into the notion of the “active ear.” Manifesting as an idiosyncratic array of spectral peaks unique to a given ear, individual SOAE peaks have nonstationary properties (e.g., amplitude and frequency modulations). Further, it has been demonstrated that interpeak relations between these “AM” and “FM” properties can be correlated, indicative of coupling of the underlying generation mechanisms. This study takes a comparative approach to characterizing these correlations in a wide variety of species exhibiting SOAEs (humans, birds, lizards) despite relatively disparate inner ear morphologies. Initial results are consistent with previous reports (e.g., van Dijk and Wit, 1990, 1998) in that SOAE interpeak correlations for a given ear are themselves idiosyncratic: Sometimes peaks (adjacent or not) exhibit correlated (positive or negative) AM and/or FM fluctuations with delays up to the order of milliseconds (typically longer for humans, shorter for lizards), while sometimes no correlation is observed. We explore implications for how such may constrain models treating the inner ear as a spatially distributed tonotopic system (e.g., various biophysical roles for coupling).
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".