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Record W2605194630 · doi:10.1097/mao.0000000000001410

Evaluation of Cochlear Duct Length Computations Using Synchrotron Radiation Phase-Contrast Imaging

2017· article· en· W2605194630 on OpenAlexaff
Robert Koch, Mai Elfarnawany, Ning Zhu, Hanif M. Ladak, Sumit Agrawal

Bibliographic record

VenueOtology & Neurotology · 2017
Typearticle
Languageen
FieldNeuroscience
TopicHearing Loss and Rehabilitation
Canadian institutionsCanadian Light Source (Canada)Western University
Fundersnot available
KeywordsMedicineSynchrotron radiationCochlear ductNuclear medicineCochleaOpticsPhysicsAnatomy

Abstract

fetched live from OpenAlex

HYPOTHESIS: Evaluation of cochlear duct length (CDL) using novel imaging techniques will help improve the accuracy of existing CDL equations. BACKGROUND: Various relationships relating A value measured from a patient's computed tomography scan and CDL have been proposed to aid in preoperative electrode selection and frequency mapping. METHODS: Ten cadaveric temporal bones were scanned using synchrotron radiation phase-contrast imaging. Reference CDL values were calculated by placing points representing the organ of Corti (OC), lateral wall (LW), and electrode location (I) on the synchrotron radiation phase-contrast imaging slices along the length of the cochlea. The CDL estimates from the existing three equations (OC, LW, I) in addition to two newly proposed equations (OC and LW) were compared with reference CDL values at each respective location. RESULTS: When compared with reference CDL values, the new OC equation improved the CDL estimates from a 6.2% error to a 5.1% error while the new LW equation improved the CDL estimate error from 3.9 to 3.6%. Bland-Altman plots revealed both new equations increased similarity to reference values and brought more samples to within clinically significant ranges. Validation of the original electrode location equation to the reference values showed a 4.6% difference. CONCLUSION: The newly proposed equations for LW and OC provided an improvement over past equations for determining CDL from the A value by showing improved agreement with reference values. Therefore, these equations can provide quick and accurate preoperative estimates of CDL for improving customized frequency mapping.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.851
Threshold uncertainty score0.663

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.097
GPT teacher head0.408
Teacher spread0.310 · 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

Citations73
Published2017
Admission routes1
Has abstractyes

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