Reliability of remote National Alzheimer's Coordinating Center Uniform Data Set data
Bibliographic record
Abstract
INTRODUCTION: The National Alzheimer's Coordinating Center (NACC) Uniform Data Set (UDS) neuropsychological battery is being used to track cognition in participants across the country, but it is unknown if scores obtained through remote administration can be combined with data obtained in person. METHODS: The remote UDS battery includes the blind version of the Montreal Cognitive Assessment (MoCA), Number Span, Semantic and Phonemic Fluency, and Craft Story. For these tests, we assessed intraclass correlation coefficients (ICCs) between in-person and remote scores in 3838 participants with both in-person and remote UDS assessments, and we compared annual score changes between modalities in a subset that had two remote assessments. RESULTS: All tests exhibited moderate to good reliability between modalities (ICCs = 0.590-0.787). Annual score changes were also comparable between modalities except for Craft Story Immediate Recall, Semantic Fluency, and Phonemic Fluency. DISCUSSION: Our findings generally support combining remote and in-person scores for the majority of UDS tests.
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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 | 0.038 | 0.107 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".