MétaCan
Menu
Back to cohort
Record W2078330375 · doi:10.3766/jaaa.18.7.2

The Role of Cognition in Age-Related Hearing Loss

2007· article· en· W2078330375 on OpenAlexaff
Fergus I. M. Craik

Bibliographic record

VenueJournal of the American Academy of Audiology · 2007
Typearticle
Languageen
FieldNeuroscience
TopicHearing Loss and Rehabilitation
Canadian institutionsBaycrest Hospital
Fundersnot available
KeywordsCognitionPsychologyHumanitiesComprehensionPerspective (graphical)ArtPhilosophyLinguistics

Abstract

fetched live from OpenAlex

The article presents a commentary on the accompanying six papers from the perspective of a cognitive psychologist. Treisman's (1964, 1969) levels of analysis model of selective attention is suggested as a framework within which the interactions between 'bottom-up' auditory factors and 'top-down' cognitive factors may be understood. The complementary roles of auditory and cognitive aspects of hearing are explored, and their mutually compensatory properties discussed. The findings and ideas reported in the six accompanying papers fit well into such a 'levels of processing' framework, which may therefore be proposed as a model for understanding the effects of aging on speech processing and comprehension. El artículo presenta un comentario sobre los seis trabajos acompañantes desde la perspectiva de un psicólogo de la cognición. Se sugiere el modelo de Treisman (1964, 1969) de niveles de análisis de la atención selectiva como el marco dentro del cuál las interacciones entre los factores de atención "de abajo hacia arriba" y los factores cognitivos de "de arriba hacia abajo" pueden ser comprendidos. Se exploran los papeles complementarios de los aspectos auditivos y cognitivos de la audición y se discuten sus mutuas propiedades compensatorias. Los hallazgos e ideas reportados en los seis trabajos acompañantes calzan bien en dicho marco de "niveles de procesamiento", los que puede, por tanto, ser propuestos como un modelo para comprender el efecto del envejecimiento para el procesamiento y la comprensión del lenguaje.

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)0.002
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 score0.806
Threshold uncertainty score0.471

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.022
GPT teacher head0.320
Teacher spread0.298 · 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

Citations52
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the American Academy of AudiologySame topicHearing Loss and RehabilitationFrench-language works237,207