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Record W2028983279 · doi:10.1017/s1355617702813200

Memory in multiple sclerosis: Contextual encoding deficits

2002· article· en· W2028983279 on OpenAlexaff
Allen E. Thornton, Naftali Raz, KAREN A. TUCKER

Bibliographic record

VenueJournal of the International Neuropsychological Society · 2002
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsEncoding (memory)MnemonicAffect (linguistics)CognitionPsychologyEpisodic memoryCognitive psychologyEncoding specificity principleComputer scienceNeuroscienceCommunication

Abstract

fetched live from OpenAlex

Long-term memory (LTM) is one of the diverse cognitive functions adversely affected by multiple sclerosis (MS). The LTM deficits have often been attributed to failure of retrieval, whereas encoding processes are presumed intact. However, support for this view comes primarily from studies in which encoding and retrieval operations were not investigated systematically. In the current study, we used an encoding specificity paradigm to examine the robustness of encoding in MS and to specifically evaluate the impact of the disease on contextual memory. We hypothesized that persons with MS would exhibit a selective impairment in retrieving items from LTM when required to generate new cue-target associations at encoding, but not when cues held a strong preexisting relationship to the targets. The findings supported the hypotheses. We conclude that the mnemonic deficits associated with MS affect both encoding and retrieval. Specifically, problems with binding of contextual information at encoding impair effective retrieval of memories. Nonetheless, access to these memories can be gained through preexisting associations organized in the semantic network.

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)0.003
Version: codex-gemma-dda1882f352aValidation 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 score0.606
Threshold uncertainty score0.446

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.185
GPT teacher head0.332
Teacher spread0.147 · 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

Citations90
Published2002
Admission routes1
Has abstractyes

Explore more

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