Bibliographic record
Abstract
The Mini-Mental State Examination (MMSE) is a widely used screening tool for evaluating cognitive decline in various clinical settings. However, there is growing evidence that the MMSE may not be as effective in detecting the early stages of cognitive impairment, such as mild cognitive impairment (MCI) or subjective cognitive decline (SCD). Several studies have suggested that the MMSE has lower sensitivity in detecting MCI compared to other neuropsychological tests, such as the Montreal Cognitive Assessment (MoCA) and the Addenbrooke’s Cognitive Examination (ACE-R). Additionally, the MMSE may not be sensitive enough to detect SCD, which is a subjective complaint of cognitive decline without objective impairment on neuropsychological tests. Despite these limitations, the MMSE remains a viable option for detecting major neurocognitive disorders, such as dementia, and it may still have a role in certain clinical contexts. Therefore, it is important to consider the specific context and purpose of the evaluation when selecting a screening tool for cognitive decline.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".