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Record W3177356734 · doi:10.1016/j.nbas.2021.100018

Hearing loss is associated with gray matter differences in older adults at risk for and with Alzheimer’s disease

2021· article· en· W3177356734 on OpenAlexafffund
Nathalie Giroud, M. Kathleen Pichora‐Fuller, Paul Mick, Walter Wittich, Faisal Al‐Yawer, Sana Rehan, J. B. Orange, Natalie A. Phillips

Bibliographic record

VenueAging Brain · 2021
Typearticle
Languageen
FieldNeuroscience
TopicHearing Loss and Rehabilitation
Canadian institutionsJewish General HospitalUniversity of TorontoUniversité de MontréalUniversity of SaskatchewanWestern UniversityConcordia UniversityCentre for Research on Brain Language and Music
FundersCanadian Institutes of Health ResearchCanada Foundation for InnovationNational Science FoundationGovernment of CanadaSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungConsortium canadien en neurodégénérescence associée au vieillissement
KeywordsAudiologyDementiaHearing lossCognitive declinePsychologyMedicineDiseaseInternal medicine

Abstract

fetched live from OpenAlex

Using data from the COMPASS-ND study we investigated associations between hearing loss and hippocampal volume as well as cortical thickness in older adults with subjective cognitive decline (SCD), mild cognitive impairment (MCI), and Alzheimer's dementia (AD). SCD participants with greater pure-tone hearing loss exhibited lower hippocampal volume, but more cortical thickness in the left superior temporal gyrus and right pars opercularis. Greater speech-in-noise reception thresholds were associated with lower cortical thickness bilaterally across much of the cortex in AD. The AD group also showed a trend towards worse speech-in-noise thresholds compared to the SCD group.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.024
GPT teacher head0.262
Teacher spread0.238 · 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 designObservational
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

Citations23
Published2021
Admission routes2
Has abstractyes

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