Research Article Rapid Screening for Cognitive Impairment in Parkinson’s Disease: A Pilot Study YanHong Dong,1,2,3,4 Way Inn Koay,1
Bibliographic record
Abstract
Copyright © 2015 YanHong Dong et al.This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Aim.This study sought to establish the discriminant validity of a rapid cognitive screen, that is, theNational Institute ofNeurological Disease and Stroke-Canadian Stroke Network (NINDS-CSN) 5-minute protocol, and compare its discriminant validity to the Montreal Cognitive Assessment (MoCA) and Mini Mental State Examination (MMSE) in detecting cognitive impairment (CI) in PD patients. Methods. One hundred and one PD patients were recruited from a movement disorders clinic in Singapore and they received the NINDS-CSN 5-minute protocol, MoCA, and MMSE. No cognitive impairment (NCI) was defined as Clinical Dementia Rating (CDR) = 0 and CI was defined as CDR ≥ 0.5. Results. Area under the receiver operating characteristic curve of NINDS-CSN 5-minute protocol was statistically equivalent to MoCA and larger than MMSE (0.86 versus 0.90,
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".