Auditory cellular cooperativity probed via spontaneous otoacoustic emissions
Bibliographic record
Abstract
As a sound pressure detector that uses energy to boost both its sensitivity and selectivity, the inner ear is an active nonequilibrium system. The collective processes of the inner ear that give rise to this exquisite functionality remain poorly understood. One manifestation of the active ear across the animal kingdom is the presence of spontaneous otoacoustic emission (SOAE), idiosyncratic arrays of spectral peaks that can be measured using a sensitive microphone in the ear canal. Current SOAE models attempt to explain how multiple peaks arise, and generally assume a spatially distributed tonotopic system. However, the nature of the generators, their coupling, and the role of noise (e.g., Brownian motion) are hotly debated, especially given the inner ear morphological diversity across vertebrates. One means of probing these facets of emission generation is studying fluctuations in SOAE peak properties, which produce amplitude and frequency modulations (AM and FM, respectively). These properties are likely related to the presence of noise affecting active cellular generation elements, and the coupling between generators. To better biophysically constrain models, this study characterizes the fluctuations in filtered SOAE peak waveforms, focusing on interrelations within and across peaks. A systematic approach is taken, examining three species that exhibit disparate inner ear morphologies: humans, barn owls, and green anole lizards. To varying degrees across all three groups, SOAE peaks have intrapeak (IrP) and interpeak (IPP) correlations indicative of interactions between generative elements. Activity from anole lizards, whose auditory sensory organ is relatively much smaller than that of humans or barn owls, showed a much higher incidence of nearest-neighbor IPP correlations. We propose that these data reveal characteristics of SOAE cellular generators acting cooperatively, allowing the ear to function as an optimized detector.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".