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Record W2008362650 · doi:10.1080/13825585.2013.772557

Age-related elevations in intraindividual variability on associative memory tasks

2013· article· en· W2008362650 on OpenAlexaff
Susan Vandermorris, Kelly J. Murphy, Angela K. Troyer

Bibliographic record

VenueAging Neuropsychology and Cognition · 2013
Typearticle
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsUniversity of TorontoBaycrest Hospital
Fundersnot available
KeywordsCognitionCognitive declineConceptualizationAudiologyExecutive functionsFrontal lobePsychologyCognitive agingCognitive psychologyMedicineDevelopmental psychologyNeuroscienceComputer scienceDementiaInternal medicineArtificial intelligence

Abstract

fetched live from OpenAlex

Age-related elevations in cognitive intraindividual variability (IIV) have been linked to reduced executive control associated with decline in frontal lobe function. However, the theoretical conceptualization of IIV in cognitive aging may be constrained by limited study of the extent to which age-related elevations in IIV may be observed on cognitive processes sensitive to aging, but not primarily reliant on frontal systems. To address this empirical gap, the present study investigated age-related differences in IIV on two associative memory tasks. Older adults showed elevated IIV on both tasks compared to younger adults. Elevated IIV was correlated with slowed response speed across both groups and tasks; IIV-accuracy correlations were mixed. Findings suggest that IIV may reflect age-related decline in distributed neural networks, including medial temporal regions, in addition to frontal systems dysfunction.

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)0.002
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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.031
GPT teacher head0.279
Teacher spread0.248 · 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

Citations15
Published2013
Admission routes1
Has abstractyes

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