The Q* Index: A Useful Global Measure of Dementia Screening Test Accuracy
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: Single, global or unitary, indicators of test diagnostic performance have intuitive appeal for clinicians. The Q* index, the point in receiver operating characteristic (ROC) curve space closest to the ideal top left-hand corner and where test sensitivity and specificity are equal, is one such measure. METHODS: Datasets from four pragmatic accuracy studies which examined the Mini-Mental State Examination, Addenbrooke's Cognitive Examination-Revised, Montreal Cognitive Assessment, Test Your Memory test, and Mini-Addenbrooke's Cognitive Examination were examined to calculate and compare the Q* index, the maximal correct classification accuracy, and the maximal Youden index, as well as the sensitivity and specificity at these cutoffs. RESULTS: Tests ranked similarly for the Q* index and the area under the ROC curve (AUC ROC). The Q* index cutoff was more sensitive (and less specific) than the maximal correct classification accuracy cutoff, and less sensitive (and more specific) than the maximal Youden index cutoff. CONCLUSION: The Q* index may be a useful global parameter summarising the test accuracy of cognitive screening instruments, facilitating comparison between tests, and defining a possible test cutoff value. As the point of equal sensitivity and specificity, its use may be more intuitive and appealing for clinicians than AUC ROC.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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