Written Spelling in Patients with Subcortical Vascular Dementia and Subcortical Vascular Mild Cognitive Impairment
Bibliographic record
Abstract
Objectives: The purpose of this study is to examine the spelling processing patterns in patients with subcortical vascular dementia (SVaD) and subcortical vascular mild cognitive impairment (svMCI).Methods: The subjects consisted of 10 patients with SVaD, 15with svMCI, and 30 normal controls (NC) subjects. Prior to this study, Korean- Mini Mental Status Examination (K-MMSE), Montreal Cognitive Assessment (MoCA-K), and health screening questionnaires were conducted as pre-tests. After that, subjects were presented with 20 words grouped according to word type (regular word, irregular word, non-word), and then they were asked to dictate the words they heard. After the tests were completed, the number of correct responses and the number of error patterns were compared between groups.Results: First, by word type between groups, the svMCI and SVaD groups showed a significantly lower number of correct responses for regular and irregular words compared to the NC group. In addition, the SVaD group showed a significantly lower number of forward responses than the svMCI group in irregular words. Non-words showed significantly lower number of forward responses in the SVaD group compared to the NC and svMCI groups. Second, the comparison of the number of error types between groups showed a significant difference between the three groups in terms of grapheme substitution; and the SVaD group showed significantly more errors compared with the NC and svMCI groups in addition and omission of graphemes. Third, the SVaD group showed significantly more errors in comparison to the NC and svMCI groups for phonological implausible errors, and the svMCI and SVaD groups showed significantly more errors than the NC group for phonological plausible errors. Fourth, lexicalization errors within non-words were observed only in the SVaD group.Conclusion: For early detection of svMCI, it is necessary to pay attention to irregular word performance.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".