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Record W2609110440 · doi:10.3233/jad-161241

The Association between Montreal Cognitive Assessment Memory Scores and Hippocampal Volume in a Neurodegenerative Disease Sample

2017· article· en· W2609110440 on OpenAlexaboutno aff
Aaron Ritter, Nanako A Hawley, Sarah J. Banks, Justin B. Miller

Bibliographic record

VenueJournal of Alzheimer s Disease · 2017
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
FundersNational Institute of General Medical Sciences
KeywordsMontreal Cognitive AssessmentHippocampal formationRecallCognitionAudiologyPsychologyAssociation (psychology)Effects of sleep deprivation on cognitive performanceAtrophyHippocampusMedicineNeuroscienceCognitive impairmentInternal medicineCognitive psychology

Abstract

fetched live from OpenAlex

Despite widespread use, there have been few investigations into the neuroanatomical correlates of the Montreal Cognitive Assessment (MoCA). In a sample of 138 consecutive patients presenting with cognitive complaints, we report significant correlations between lower MoCA memory scores and smaller hippocampal volumes (r = 0.36-0.41, p < 0.001). We also report that the newly devised memory index score, designed to better capture encoding deficits than the standard delayed recall score, was not significantly better for predicting hippocampal volume. These initial results suggest that poor performance on the MoCA's memory section should prompt further evaluation for hippocampal atrophy.

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 score0.013
Threshold uncertainty score0.025

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 communication0.0000.000
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 head0.028
GPT teacher head0.348
Teacher spread0.320 · 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

Citations43
Published2017
Admission routes1
Has abstractyes

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