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Record W2151398446 · doi:10.1017/s1355617706060632

Subject-performed tasks improve associative learning in amnestic mild cognitive impairment

2006· article· en· W2151398446 on OpenAlexafffund
Stella Karantzoulis, Jill B. Rich, Jennifer A. Mangels

Bibliographic record

VenueJournal of the International Neuropsychological Society · 2006
Typearticle
Languageen
FieldNeuroscience
TopicMemory and Neural Mechanisms
Canadian institutionsBaycrest HospitalYork University
FundersYork University
KeywordsEpisodic memoryAssociative propertyPsychologyCognitive psychologyRecallCognitionSemantic memoryInterference theoryWorking memoryNeuroscience

Abstract

fetched live from OpenAlex

Subject-performed tasks (SPTs) may facilitate the deficit in associative learning among individuals with amnestic mild cognitive impairment (aMCI) by inducing episodic integration of object-action associations. To test this hypothesis, we examined free recall and recognition memory following enactment and verbal encoding in healthy elderly controls and individuals with aMCI. Study lists contained either semantically integrated ("Bounce the ball") or crossed object-action commands, in which episodic and semantic associations were placed in opposition ("Pet the compass"). Associative learning was indeed better after SPT than verbal encoding and with integrated relative to crossed lists for the aMCI group, as it was for controls. Moreover, the degree to which SPTs reduced the semantic interference inherent in the crossed conditions was equivalent for the two groups. The results showed that enactment facilitates formation of episodic associations, even when not supported by preexisting semantic knowledge, and even among individuals who have particular difficulty forming new associations.

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)0.000
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
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 head0.049
GPT teacher head0.324
Teacher spread0.275 · 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

Citations10
Published2006
Admission routes2
Has abstractyes

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