Comparing Diagnostic Accuracy of Cognitive Screening Instruments: A Weighted Comparison Approach
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND/AIMS: There are many cognitive screening instruments available to clinicians when assessing patients' cognitive function, but the best way to compare the diagnostic utility of these tests is uncertain. One method is to undertake a weighted comparison which takes into account the difference in sensitivity and specificity of two tests, the relative clinical misclassification costs of true- and false-positive diagnosis, and also disease prevalence. METHODS: Data were examined from four pragmatic diagnostic accuracy studies from one clinic which compared the Mini-Mental State Examination (MMSE) with the Addenbrooke's Cognitive Examination-Revised (ACE-R), the Montreal Cognitive Assessment (MoCA), the Test Your Memory (TYM) test, and the Mini-Mental Parkinson (MMP), respectively. RESULTS: Weighted comparison calculations suggested a net benefit for ACE-R, MoCA, and MMP compared to MMSE, but a net loss for TYM test compared to MMSE. CONCLUSION: Routine incorporation of weighted comparison or other similar net benefit measures into diagnostic accuracy studies merits consideration to better inform clinicians of the relative value of cognitive screening instruments.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it