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Record W4390673784 · doi:10.1002/lary.31263

Morphologic Analysis of the Scala Tympani Using Synchrotron: Implications for Cochlear Implantation

2024· article· en· W4390673784 on OpenAlexafffund
Ashley N. Micuda, Hao Li, Helge Rask‐Andersen, Hanif M. Ladak, Sumit Agrawal

Bibliographic record

VenueThe Laryngoscope · 2024
Typearticle
Languageen
FieldNeuroscience
TopicHearing Loss and Rehabilitation
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of CanadaVetenskapsrådetCanadian Institutes of Health ResearchStiftelsen Tysta SkolanCanadian Light Source
KeywordsCochlear ductRound windowCochleaCadaveric spasmElectrode arrayCochlear implantLateral wallCochlear implantationMaterials scienceAnatomyElectrodeBiomedical engineeringAudiologyMedicinePhysics

Abstract

fetched live from OpenAlex

OBJECTIVES: To use synchrotron radiation phase-contrast imaging (SR-PCI) to visualize and measure the morphology of the entire cochlear scala tympani (ST) and assess cochlear implant (CI) electrode trajectories. METHODS: SR-PCI images were used to obtain geometric measurements of the cochlear scalar diameter and area at 5-degree increments in 35 unimplanted and three implanted fixed human cadaveric cochleae. RESULTS: The cross-sectional diameter and area of the cochlea were found to decrease from the base to the apex. This study represents a wide variability in cochlear morphology and suggests that even in the smallest cochlea, the ST can accommodate a 0.4 mm diameter electrode up to 720°. Additionally, all lateral wall array trajectories were within the anatomically accommodating insertion zone. CONCLUSION: This is the first study to use SR-PCI to visualize and quantify the entire ST morphology, from the round window to the apical tip, and assess the post-operative trajectory of electrodes. These high-resolution anatomical measurements can be used to inform the angular insertion depth that can be accommodated in CI patients, accounting for anatomical variability. LEVEL OF EVIDENCE: N/A. Laryngoscope, 134:2889-2897, 2024.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.906
Threshold uncertainty score0.204

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.069
GPT teacher head0.353
Teacher spread0.284 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations18
Published2024
Admission routes2
Has abstractyes

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