The AVERT MoCA Data: Scoring Reliability in a Large Multicenter Trial
Bibliographic record
Abstract
The Montreal Cognitive Assessment (MoCA) is a widely used cognitive screening tool in stroke. As scoring the visuospatial/executive MoCA items involves subjective judgement, reliability is important. Analyzing data on these items from A Very Early Rehabilitation Trial (AVERT), we compared the original scoring of assessors ( n = 102) to blind scoring by a single, independent rater. In a sample of scoresheets from 1,119 participants, we found variable interrater reliability. The match between original assessors and the independent rater was the following: trail-making 97% (κ = 0.94), cube copy 90% (κ = 0.80), clock contour 92% (κ = 0.49), clock numbers 89% (κ = 0.67), and clock hands 72% (κ = 0.46). For all items except clock contour, the independent rater was “stricter” than the original assessors. Discrepancies were typically errors in original scoring, rather than borderline differences in subjective judgement. In trials that include the MoCA, researchers should emphasize scoring rules to assessors and implement independent data checking, especially for clock hands, to maximize accuracy.
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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 | 0.074 | 0.130 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".