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Record W2037787284 · doi:10.1080/138255890969302

Interference Resolution in the Elderly: Evidence Suggestive of Differences in Strategy on Measures of Prepotent Inhibition and Dual Task Processing

2006· article· en· W2037787284 on OpenAlexaff
P. Vivien Rekkas

Bibliographic record

VenueAging Neuropsychology and Cognition · 2006
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsYork University
Fundersnot available
KeywordsTask (project management)PsychologyDistractionCognitionWorking memoryInterference theoryMemory spanCognitive psychologyDual (grammatical number)Interference (communication)Test (biology)Balance (ability)Developmental psychologyAudiologyComputer scienceMedicineNeuroscience

Abstract

fetched live from OpenAlex

The ability to effectively resolve interference was investigated in young and elderly participants using a test of inhibition and a dual task measure. The tasks stressed the ability to suppress prepotent responding, and balance primary and secondary task demands, respectively. Successful performance on both measures hinged on the ability to minimize the distraction generated between competing aspects of each task. Increasing demands resulted in performance decrements despite titration for individual differences in span size and generalized slowing. These were more pronounced on the hardest condition of each task, especially in older participants. Furthermore, the nature of the decrements suggested the use of different strategies between groups. It is argued that a fundamental source of the age-associated variability in cognition is due to compromised ability to effectively resolve interference, and cannot be sufficiently explained by memory span differences or generalized slowing.

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)0.003
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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.197
GPT teacher head0.357
Teacher spread0.160 · 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

Citations8
Published2006
Admission routes1
Has abstractyes

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