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Record W3160043982 · doi:10.9734/bpi/rrab/v6/1607f

On the Molecular Filters in Cochlea Transduction: A Scientific Explanation

2021· book-chapter· en· W3160043982 on OpenAlexaff
Valeri Goussev

Bibliographic record

VenueBook Publisher International (a part of SCIENCEDOMAIN International) · 2021
Typebook-chapter
Languageen
FieldHealth Professions
TopicNoise Effects and Management
Canadian institutionsJewish Rehabilitation Hospital
Fundersnot available
KeywordsBasilar membraneCochleaTransduction (biophysics)Tectorial membraneHair cellStereocilia (inner ear)Inner earAcousticsPhysicsMechanism (biology)BiophysicsEngineeringNeuroscienceBiologyMechanical engineering

Abstract

fetched live from OpenAlex

The article is devoted to the specific consideration of the cochlear transduction for the low level sound intensities, which correspond to the regions near the perception threshold. The basic cochlea mechanics is extended by the new concept of the molecular filters, which allows discussing the transduction mechanism on the molecular level in the space?time domain. The molecular filters are supposed to be built on the set of the stereocilia of every inner hair cell. It is hypothesized that the molecular filters are the sensors in the feedback loop, which includes also outer hair cells along with the tectorial membrane and uses the zero compensation method to evaluate the traveling wave shape on the basilar membrane. Besides the compensation, the feedback loop, being spatially distributed along the cochlea, takes control over the tectorial membrane strain field generated by the outer hair cells, and implements it as the mechanism for the automatic gain control in the sound transduction. The numerical simulations of the traveling waves for the real sound intensities also    confirm the low values of the basilar membrane deformations.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.702
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0190.000

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.

Opus teacher head0.044
GPT teacher head0.335
Teacher spread0.290 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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