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Record W2900959292 · doi:10.1037/pag0000303

Age-related decline in item but not spatiotemporal associative memory for a real-world event.

2018· article· en· W2900959292 on OpenAlexafffund
Nicholas B. Diamond, Kristoffer Romero, Nivethika Jeyakumar, Brian Levine

Bibliographic record

VenuePsychology and Aging · 2018
Typearticle
Languageen
FieldPsychology
TopicIdentity, Memory, and Therapy
Canadian institutionsUniversity of TorontoBaycrest Hospital
FundersCanadian Institutes of Health Research
KeywordsPsychologyEpisodic memoryPsycINFOContext (archaeology)Cognitive psychologyContent-addressable memoryForgettingAssociative propertyRecognition memoryDevelopmental psychologyCognitionNeuroscienceArtificial intelligenceComputer science

Abstract

fetched live from OpenAlex

Normal aging is typically associated with reduced ability to reconstruct the spatiotemporal context of past events, a core component of episodic memory. However, little is known about our ability to remember the order of events comprising extended real-world experiences and how this ability changes with age. We leveraged the richness and structure of a museum exhibit to address this question. Three months after visiting the exhibit, 141 adults aged 18-84 completed a test of spatiotemporal order memory and old/new recognition using pictures from the exhibit and similar lures, from which measures of associative and item memory were derived. Order discrimination accuracy was modulated by interitem order and distance in younger and older adults, extending findings from recognition of laboratory stimuli at short delays to remote real-world experiences. In contrast to established findings from laboratory-based assessments, we observed a significant effect of aging on item memory driven by increased lure susceptibility, but no age-related reduction in spatiotemporal associative memory. These findings present novel insights into different components of memory for real-world experiences at naturalistic timescales and across the lifespan. (PsycINFO Database Record (c) 2018 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.229
Threshold uncertainty score0.796

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.041
GPT teacher head0.398
Teacher spread0.358 · 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.

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

Citations14
Published2018
Admission routes2
Has abstractyes

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