Bibliographic record
Abstract
There are multiple brief cognitive screening measures that can be used in studies of cognitive functioning in PD. These scales supply an adequate assessment of cognitive functioning that can be accomplished within a standard clinical or research visit. From a search of the existing literature, 12 cognitive screening measures were identified that assessed multiple cognitive domains and could be completed within a standard clinical visit (less than one hour). Recommendations for use of the 12 screening measures were based on three separate criteria: use in PD cohorts, wide application of the scale beyond the scale developers, and sufficient clinimetric strength to warrant its use, based on studies in cognitively impaired populations, preferably with PD. Seven scales can be recommended for use in PD: Addenbrooke’s Cognitive Examination; Alzheimer’s Disease Assessment Scale–Cognition; Dementia Rating Scale; Montreal Cognitive Examination; Repeatable Battery for the Assessment of Neuropsychological Status; and Scales for Outcomes of Parkinson’s Disease–Cognition. Three scales can be suggested for use in PD: Mini-Mental State Examination; Parkinson’s Disease Cognitive Rating Scale; and Parkinson Neuropsychometric Dementia Assessment. A number of the other scales with limited information at this time may achieve these designations with future studies. These rankings are offered for individuals deciding on which cognitive screening scale to use in a given clinical or research situation.
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 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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.044 | 0.019 |
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".