Assessment of cube‐copying among community‐dwelling elderly living in Japan using the vertex criterion and parallelism
Bibliographic record
Abstract
BACKGROUND: The cube-copying test is used to assess cognitive function. It is one of the methods used to distinguish healthy older individuals from those with cognitive impairment based on its 3 mm vertex criterion and parallel line errors. We sought to assess how: (1) precisely elderly community-dwelling individuals draw cubes based on two different vertex criteria; and (2) they keep the parallelism of lines. METHODS: The cross-sectional design study population comprised 121 adults ((outlier analysis excluded the results of three, resulting in 118 participants) ≥ 65 years (21 men and 100 women) who participated in an annual physical fitness circuit and who lived independently in their communities. We recorded the participants' ages, years of education, and the scores they obtained in the Japanese version of the Montreal Cognitive Assessment. Participants were instructed to draw the cube as precisely as possible. Cube drawings were assessed based on the correct position of the vertices using 1 and 3 mm criteria and parallel line errors. RESULTS: Eighty-nine percent of the participants were able to draw vertices within 3 mm distance from the correct position but found it difficult to draw them within 1 mm distance. Using the 3 mm vertex criterion, the mean score for correct vertices was six (out of a maximum of eight). Most of the participants made a maximum of one out of six possible parallel line errors. CONCLUSIONS: Almost 90% of the elderly in our study drew the vertices within 3 mm of the correct position, and the parallel line errors were few. The 3 mm vertex and parallel line criteria by cube-copying seem to be cleared by most community-dwelling elderly. Further research should determine if participants aged ≥85 years with less than 6 years of education show different results.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".