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Record W2127742203 · doi:10.1177/0194599814547475

Clinical Practice Guideline: Tinnitus Executive Summary

2014· article· en· W2127742203 on OpenAlexaff
David E. Tunkel, Carol A. Bauer, Gordon H. Sun, Richard M. Rosenfeld, Sujana S. Chandrasekhar, Eugene R. Cunningham, Sanford M. Archer, Brian W. Blakley, John M. Carter, Evelyn Granieri, James A. Henry, Deena B. Hollingsworth, Fawad Khan, Scott Mitchell, Ashkan Monfared, Craig W. Newman, Folashade Omole, C. Douglas Phillips, Shannon K. Robinson, Malcolm B. Taw, Richard S. Tyler, Richard W. Waguespack, Elizabeth J. Whamond

Bibliographic record

VenueOtolaryngology · 2014
Typearticle
Languageen
FieldNeuroscience
TopicHearing, Cochlea, Tinnitus, Genetics
Canadian institutionsUniversity of Manitoba
FundersAmerican Academy of Otolaryngology-Head and Neck Surgery
KeywordsTinnitusGuidelineMedicineReferralPsychological interventionOtorhinolaryngologyExecutive summarySpecialtyIntensive care medicineFamily medicineAudiologyPathologySurgeryPsychiatry

Abstract

fetched live from OpenAlex

The American Academy of Otolaryngology--Head and Neck Surgery Foundation (AAO-HNSF) has published a supplement to this issue featuring the new Clinical Practice Guideline: Tinnitus. To assist in implementing the guideline recommendations, this article summarizes the rationale, purpose, and key action statements. The 13 recommendations developed address the evaluation of patients with tinnitus, including selection and timing of diagnostic testing and specialty referral to identify potential underlying treatable pathology. It will then focus on the evaluation and treatment of patients with persistent primary tinnitus, with recommendations to guide the evaluation and measurement of the impact of tinnitus and to determine the most appropriate interventions to improve symptoms and quality of life for tinnitus sufferers.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.035
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.031
Threshold uncertainty score0.102

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.035
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0050.005
Science and technology studies0.0020.001
Scholarly communication0.0030.003
Open science0.0030.002
Research integrity0.0100.009
Insufficient payload (model declined to judge)0.0310.033

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 head0.039
GPT teacher head0.362
Teacher spread0.323 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations107
Published2014
Admission routes1
Has abstractyes

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