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Record W4400016816 · doi:10.1097/aud.0000000000001526

International Consensus Statements on Intraoperative Testing for Cochlear Implantation Surgery

2024· article· en· W4400016816 on OpenAlexaff
Farid Alzhrani, Isra Aljazeeri, Yassin Abdelsamad, Abdulrahman Alsanosi, Ana H. Kim, Ángel Ramos‐Macías, Ángel Ramos de Miguel, Anja Kurz, Artur Lorens, Bruce J. Gantz, Craig A. Buchman, Dayse Távora‐Vieira, Georg Mathias Sprinzl, Griet Mertens, James E. Saunders, Julie Kosaner, Laila M. Telmesani, Luis Lassaletta, Manohar Bance, Medhat Yousef, Meredith A. Holcomb, Oliver F. Adunka, Per Cayé-Thomasen, Piotr H. Skarżyński, Ranjith Rajeswaran, Robert Briggs, Seung Ha Oh, Stefan K. Plontke, Stephen O’Leary, Sumit Agrawal, Tatsuya Yamasoba, Thomas Lenarz, Thomas Wesarg, Walter Kutz, Patrick J Connolly, Ilona Anderson, Abdulrahman Hagr

Bibliographic record

VenueEar and Hearing · 2024
Typearticle
Languageen
FieldNeuroscience
TopicHearing Loss and Rehabilitation
Canadian institutionsWestern University
FundersKing Saud University
KeywordsStatement (logic)VotingDelphi methodEvidence-based medicineConsensus conferenceSet (abstract data type)Quality (philosophy)Computer scienceMedicineDelphiMedical physicsTest (biology)MEDLINEPolitical scienceArtificial intelligenceLaw

Abstract

fetched live from OpenAlex

OBJECTIVES: A wide variety of intraoperative tests are available in cochlear implantation. However, no consensus exists on which tests constitute the minimum necessary battery. We assembled an international panel of clinical experts to develop, refine, and vote upon a set of core consensus statements. DESIGN: A literature review was used to identify intraoperative tests currently used in the field and draft a set of provisional statements. For statement evaluation and refinement, we used a modified Delphi consensus panel structure. Multiple interactive rounds of voting, evaluation, and feedback were conducted to achieve convergence. RESULTS: Twenty-nine provisional statements were included in the original draft. In the first voting round, consensus was reached on 15 statements. Of the 14 statements that did not reach consensus, 12 were revised based on feedback provided by the expert practitioners, and 2 were eliminated. In the second voting round, 10 of the 12 revised statements reached a consensus. The two statements which did not achieve consensus were further revised and subjected to a third voting round. However, both statements failed to achieve consensus in the third round. In addition, during the final revision, one more statement was decided to be deleted due to overlap with another modified statement. CONCLUSIONS: A final core set of 24 consensus statements was generated, covering wide areas of intraoperative testing during CI surgery. These statements may provide utility as evidence-based guidelines to improve quality and achieve uniformity of surgical practice.

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)0.001
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 score0.504
Threshold uncertainty score0.193

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.134
GPT teacher head0.391
Teacher spread0.257 · 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

Citations9
Published2024
Admission routes1
Has abstractyes

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