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Record W1979772717 · doi:10.1007/s00441-014-1992-8

Tinnitus: animal models and findings in humans

2014· review· en· W1979772717 on OpenAlexafffund
Jos J. Eggermont, Larry E. Roberts

Bibliographic record

VenueCell and Tissue Research · 2014
Typereview
Languageen
FieldNeuroscience
TopicHearing, Cochlea, Tinnitus, Genetics
Canadian institutionsMcMaster UniversityUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsTinnitusAuditory cortexNeuroscienceHyperacusisAuditory pathwaysAudiologyAudiogramTonotopyNeuroplasticityHearing lossPsychologyAuditory systemMedicine

Abstract

fetched live from OpenAlex

Chronic tinnitus (ringing of the ears) is a medically untreatable condition that reduces quality of life for millions of individuals worldwide. Most cases are associated with hearing loss that may be detected by the audiogram or by more sensitive measures. Converging evidence from animal models and studies of human tinnitus sufferers indicates that, while cochlear damage is a trigger, most cases of tinnitus are not generated by irritative processes persisting in the cochlea but by changes that take place in central auditory pathways when auditory neurons lose their input from the ear. Forms of neural plasticity underlie these neural changes, which include increased spontaneous activity and neural gain in deafferented central auditory structures, increased synchronous activity in these structures, alterations in the tonotopic organization of auditory cortex, and changes in network behavior in nonauditory brain regions detected by functional imaging of individuals with tinnitus and corroborated by animal investigations. Research on the molecular mechanisms that underlie neural changes in tinnitus is in its infancy and represents a frontier for investigation.

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)0.001
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.003

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 head0.325
GPT teacher head0.468
Teacher spread0.142 · 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
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

Citations152
Published2014
Admission routes2
Has abstractyes

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