Application of the Cogstate Brief Battery in assessing cognitive function in older Japanese individuals
Bibliographic record
Abstract
Background Accurate and simple detection of cognitive decline is important for the prediction of dementia and identification of drug indications. The Cogstate Brief Battery (CBB) is useful in assessing cognitive function during the preclinical and mild cognitive impairment stages. However, whether it is beneficial for assessing brain function in older Japanese adults remains unclear. Objective This study aimed to assess the association of the CBB score with those of traditional cognitive tests and brain imaging in assessing cognitive function in older Japanese adults with normal cognitive function and those with mild cognitive impairment. Methods Community-dwelling older adults in Usuki city underwent CBB, traditional cognitive tests, magnetic resonance imaging, and amyloid positron emission tomography. The association of the CBB score with the Japanese version of the Montreal Cognitive Assessment (MoCA-J), Japanese version of Mini-Mental State Examination (MMSE), hippocampal atrophy on magnetic resonance imaging, and brain amyloid deposition on 11 C-Pittsburgh compound-B positron emission tomography was examined. Results In total, 170 participants were included in this study. Among them, 59 were positive for the C-Pittsburgh compound-B. The CBB score was significantly associated with the MoCA-J and MMSE score in all patients. Further, it was significantly associated with hippocampal atrophy in the amyloid-positive group. Conclusions The CBB is associated with the MoCA-J and MMSE scores and may thus be a useful tool for the assessing cognitive decline in Japanese older adults.
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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 | 0.002 | 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".