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Record W2789904526 · doi:10.1037/pag0000220

Age differences in memory for meaningful and arbitrary associations: A memory retrieval account.

2018· article· en· W2789904526 on OpenAlexafffund
Tarek Amer, Kelly S. Giovanello, Cheryl L. Grady, Lynn Hasher

Bibliographic record

VenuePsychology and Aging · 2018
Typearticle
Languageen
FieldNeuroscience
TopicMemory Processes and Influences
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsPsycINFOPsychologyContent-addressable memoryCognitionYoung adultDevelopmental psychologyMemoriaEpisodic memoryCognitive psychologyMEDLINEArtificial intelligenceNeuroscienceComputer science

Abstract

fetched live from OpenAlex

Older adults typically show poor associative memory performance relative to younger adults. This age-related effect, however, is mediated by the meaningfulness of the materials used, such that age differences are minimized with the use of information that is consistent with prior knowledge. While this effect has been interpreted as facilitative learning through schematic support, the role of memory retrieval on this effect has yet to be explored. Using an associative memory paradigm that varied the extent of controlled retrieval for previously studied meaningful or arbitrary associations, older and younger adults in the present study retrieved realistic and unrealistic grocery item prices in a speeded, or in a slow, more control-based retrieval condition. There were no age differences in memory for realistic (meaningful) prices in either condition; however, younger adults showed better memory than older adults for unrealistic prices in the controlled retrieval condition only. These results suggest that age differences in memory for arbitrary associations can, at least partly, be accounted for by age reductions in strategic, controlled retrieval. (PsycINFO Database Record

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)0.006
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 score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.071
GPT teacher head0.348
Teacher spread0.278 · 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

Citations58
Published2018
Admission routes2
Has abstractyes

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