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Record W2026370359 · doi:10.1155/2008/859657

Patterns of Semantic Memory Impairment in Mild Cognitive Impairment

2008· article· en· W2026370359 on OpenAlexafffund
Sven Joubert, Olivier Félician, Emmanuel J. Barbeau, Mira Didic, Michel Poncet, Mathieu Ceccaldi

Bibliographic record

VenueBehavioural Neurology · 2008
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsUniversité de MontréalInstitut Universitaire de Gériatrie de Montréal
FundersAlzheimer Society
KeywordsCognitive impairmentMemory impairmentSemantic memoryCognitive psychologyPsychologyCognitionAudiologyMedicineNeuroscience

Abstract

fetched live from OpenAlex

Although the semantic memory impairment has been largely documented in Alzheimer's disease, little is known about semantic memory in the preclinical phase of the disease (Mild Cognitive Impairment). The purpose of this study was to document the nature of semantic breakdown using a battery of tests assessing different aspects of conceptual knowledge: knowledge about common objects, famous people and famous public events. Results indicate that all domains of semantic memory were impaired in MCI individuals but knowledge about famous people and famous events was affected to a greater extent than knowledge about objects. This pattern of results suggests that conceptual entities with distinctive and unique properties may be more prone to semantic breakdown in MCI. In summary, results of this study support the view that genuine semantic deficits are present in MCI. It could be useful to investigate the etiological outcome of patients failing or succeeding at such tests.

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)0.005
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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.313
Teacher spread0.273 · 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

Citations97
Published2008
Admission routes2
Has abstractyes

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