Cochlear evanescent liquid sound-pressure waves during spontaneous Oto-Acoustic emissions
Bibliographic record
Abstract
In the diagram on the left in Fig. 1, the streamlines of an evanescent (standing) liquid sound-pressure wave generated by a miniaturized and idealized underwater tuning-fork prong are shown [Frosch (2010a, 2010b)]. The prong is assumed to oscillate in the zr-direction. Liquid particles having a no-wave location on one of these streamlines stay on that line during their oscillation. In the diagram on the right in Fig. 1, the corresponding lines of constant liquid sound-pressure amplitude are displayed; see Section 2.1. In this study it is assumed that spontaneous oto-acoustic emissions (SOAEs) from the human inner ear [e.g., Frosch (2010a)] are generated, in a feedback process, by outer-hair-cell-driven localized oscillations of the basilar membrane (BM), and it is shown that a corresponding liquid motion above and below the BM of an idealized cochlear box model [cubic channel, x-independent properties] can be found by a superposition of three standing waves similar to that shown in Fig. 1, generated by a prong centred at xr = 0 and by two prongs at xr = ±a, where typically a = 0.01 mm. It is assumed that at time t = T/4 (where T = oscillation period) the central prong is at zr = +2δ and the two lateral prongs are at zr = -δ; typically, δ = 0.1 μm.
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| 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".