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Record W2945574897 · doi:10.1037/pag0000361

Associative interference in older and younger adults.

2019· article· en· W2945574897 on OpenAlexafffund
Rachel Burton, Isabel Lek, Roger A. Dixon, Jeremy B. Caplan

Bibliographic record

VenuePsychology and Aging · 2019
Typearticle
Languageen
FieldPsychology
TopicBehavioral Health and Interventions
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaNational Institute on AgingNational Institutes of Health
KeywordsPsychologyYoung adultDevelopmental psychology

Abstract

fetched live from OpenAlex

Healthy older adults are more challenged by associative interference than younger adults, but prior results could have been due to differences in list discrimination ability. We used a procedure that assessed interference without requiring knowledge of list membership to test the hypothesis that older adults (60-74 years old) would show more pronounced effects of associative interference in AB/AC learning. Despite our use of a self-paced, rather than timed, study procedure, older adults performed at lower levels of accuracy than younger adults, replicating the well established associative deficit in aging (Naveh-Benjamin & Mayr, 2018). Older participants also displayed more proactive interference on average. Older participants' memory for AB and AC showed statistical independence, resembling earlier data from younger participants with a timed study procedure (Burton, Lek, & Caplan, 2017). However, younger participants, with the current self-paced procedure, produced a facilitating relationship between memory for AB and AC. Thus, younger participants not only resolved, but reversed associative interference. List discrimination could not explain these age differences. Taken together, these results extend the associative deficit in aging, finding increased susceptibility to associative proactive interference and less resolution of associative interference in older than younger participants, even when given the opportunity to compensate during self-paced study. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.111
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.037
GPT teacher head0.414
Teacher spread0.377 · 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.

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

Citations14
Published2019
Admission routes2
Has abstractyes

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