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Declining of memory functions of normal elderly persons

2000· article· en· W2081149092 on OpenAlexaff
Masao Yokota, Kazuo Miyanaga, Kimie Yonemura, Hama Watanabe, Kiichi Nagashima, Katsuo Naito, Saburouta Yamada, Setuko Arai, Richard W. J. Neufeld

Bibliographic record

VenuePsychiatry and Clinical Neurosciences · 2000
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsWestern University
Fundersnot available
KeywordsPsychologyDementiaVerbal memoryShort-term memoryDevelopmental psychologyWechsler Adult Intelligence ScaleMemory impairmentAudiologyGerontologyWorking memoryCognitionPsychiatryMedicineDisease

Abstract

fetched live from OpenAlex

Two studies examined the declining of memory functions in normal elderly persons using the Yokota memory test (YMT), which includes 15 items concerning verbal and non-verbal memory functions. In the first study, 552 subjects over 40 years of age in five age groups were examined. Factor analysis revealed that YMT consisted of two factors pertaining to short-term/working memory, and two factors pertaining to long-term memory. It is suggested that the former was more affected than the latter, with aging. In the second study, YMT was examined in relation to the revised version of Hasegawa dementia scale (HDS-R), which was the most popular intelligence scale for the elderly in Japan. As a result, memory functions differentially declined with the decreasing score of HDS-R, which suggests that memory functions differentially declined with progressive risk of dementia.

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)0.004
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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.036
GPT teacher head0.377
Teacher spread0.341 · 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

Citations18
Published2000
Admission routes1
Has abstractyes

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