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Record W1973085419 · doi:10.3389/fneur.2014.00179

Behavioral Models of Tinnitus and Hyperacusis in Animals

2014· review· en· W1973085419 on OpenAlexaff
Sarah H. Hayes, Kelly E. Radziwon, Daniel Stolzberg, Richard Salvi

Bibliographic record

VenueFrontiers in Neurology · 2014
Typereview
Languageen
FieldNeuroscience
TopicHearing, Cochlea, Tinnitus, Genetics
Canadian institutionsWestern University
FundersOffice of Naval ResearchNational Institute on Deafness and Other Communication DisordersNational Defense Science and Engineering GraduateNational Institutes of Health
KeywordsHyperacusisTinnitusAuditory pathwaysAudiologyPsychologyMedicinePerceptionNeuroscience

Abstract

fetched live from OpenAlex

The phantom perception of tinnitus and reduced sound-level tolerance associated with hyperacusis have a high comorbidity and can be debilitating conditions for which there are no widely accepted treatments. One factor limiting the development of treatments for tinnitus and hyperacusis is the lack of reliable animal behavioral models of these disorders. Therefore, the purpose of this review is to highlight the current animal models of tinnitus and hyperacusis, and to detail the advantages and disadvantages of each paradigm. To date, this is the first review to include models of both tinnitus and hyperacusis.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.991
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.098
GPT teacher head0.348
Teacher spread0.250 · 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
GenreReview

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

Citations76
Published2014
Admission routes1
Has abstractyes

Explore more

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