Methods for Interpretation of Scores of 5 Neuropsychological Tests
Bibliographic record
Abstract
Objective: To provide methods to interpret and compare different neurobehavioral screening tests for the diagnosis of dementia. Design: Five mental-status neuropsychological tools for dementia screening were administered to patients in a memory disorder clinic. These included the Mini-Mental State Examination, the Dementia Rating Scale, the 6-item derivative of the Orientation-Memory-Concentration Test, a short Mental Status Questionnaire, and a composite tool we labeled the Ottawa Mental Status Examination, which assessed orientation, memory, attention, language, and visual-constructive functioning. Results: To obtain z and percentile scores, norms are for the different tests, computed separately for patients with dementia of the Alzheimer type, vascular dementia, or no dementia. Another set of norms is reported in which a test score is translated directly into the posttest probability of dementia. Translation formulas are given to allow the estimation of the score on one test from the result on another test. Conclusion: The interpretation of tests used to diagnose dementia must be based on an understanding of the meaning of an individual score, which is based on the question asked and the population to which the patient is referenced. Arch Neurol. 1996;53:1043-1054
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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 | 0.026 | 0.093 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 0.006 |
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".