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Record W2358573505

Analysis of neuropsychological characteristics for old patients with vascular mild cognitive impairment by MoCA scale.

2012· article· en· W2358573505 on OpenAlexaboutno aff
Tian Chun-ya

Bibliographic record

VenueHainan yixue · 2012
Typearticle
Languageen
FieldNeuroscience
TopicNeurological Disease Mechanisms and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMontreal Cognitive AssessmentMedicineNeuropsychologyCognitive impairmentCognitionExecutive functionsNeuropsychological assessmentNeuropsychological testingAudiologyPsychiatry
DOInot available

Abstract

fetched live from OpenAlex

Objective To study the neuropsychological characteristics for old patients with vascular mild cognitive impairment (vMCI) with MoCA scale in order to provide science evidence for early discovery, diagnosis and intervention of vMCI. Methods The vMCI patients who accepted therapy in our hospital from January 2010 to May 2011 were surveyed by Montreal Cognitive Assessment (MoCA). Results The accuracy rate of MoCA was 97.3%. Age, educational level and occupation significantly influenced the score of MoCA (P 0.05). The score of delayed remember, attention and visual space were the lowest percentage of their own total score, as 31.40%, 65.17% and 69.00%. Conclusion MoCA was a good tool to screen the vMCI, and it should be widely applied. In addition, the neuropsychological characteristics of vMCI were heavier damage in visual space and executive ability, attention and delayed memory and so on.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.018
Threshold uncertainty score0.601

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
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)0.0000.000

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 head0.018
GPT teacher head0.256
Teacher spread0.237 · 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

Citations0
Published2012
Admission routes1
Has abstractyes

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