MétaCan
Menu
Back to cohort
Record W2098973596 · doi:10.1080/13825580903165428

Sequential Performance in Young and Older Adults: Evidence of Chunking and Inhibition

2009· article· en· W2098973596 on OpenAlexaff
Karen Li, Mervin Blair, Virginia Chow

Bibliographic record

VenueAging Neuropsychology and Cognition · 2009
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsConcordia University
Fundersnot available
KeywordsChunking (psychology)PerseverationSequence (biology)PsychologyDevelopmental psychologyCognitive psychologyBiologyGeneticsCognitionNeuroscience

Abstract

fetched live from OpenAlex

Two experiments were conducted to examine possible sources of age-related decline in sequential performance: age differences in sequence representation, retrieval of sequence elements, and efficiency of inhibitory processes. Healthy young and older participants learned a sequence of eight animal drawings in fixed order, then monitored for these targets within trials of mis-ordered stimuli, responding only when targets were shown in the correct order. Responses were slower for odd numbered targets, suggesting that participants spontaneously organized the sequence in two-element chunks. Perseverations (responses to previously relevant targets) served as an index of inhibitory inefficiency. Efficiency of chunk retrieval and self-inhibition were lower for older than for younger adults. Increasing environmental support in Experiment 2 through overt articulation of current chunk elements showed a pattern of results similar to Experiment 1, with particular benefit for older adults. The findings suggest an underlying susceptibility to interference in old age.

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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
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)0.0020.000

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 head0.069
GPT teacher head0.347
Teacher spread0.277 · 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

Citations7
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueAging Neuropsychology and CognitionSame topicNeural and Behavioral Psychology StudiesFrench-language works237,207