Generalization of Youden index for multiple‐class classification problems applied to the assessment of externally validated cognition in Parkinson disease screening
Bibliographic record
Abstract
Routine cognitive screening in Parkinson disease (PD) has become essential for management, to track progression and to assess clinical status in therapeutic trials. Patients with mild cognitive impairment (PD-MCI) are more likely to progress to dementia and therefore need to be distinguished from patients with normal cognition and those with dementia. A three-class Youden index has been recently proposed to select cut-off points in three-class classification problems. In this article, we examine properties of a modification of the three-class Youden index and propose a generalization to k-class classification problems. Geometric and theoretical properties of the modified index J(k) are examined. It is shown that J(k) is equivalent to the sum of the k - 1 two-class Youden indices for the adjacent classes of the ordered alternative problem given that the ordering holds. Methods are applied in the assessment of the Montreal Cognitive Assessment test when screening cognition in PD.
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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 | 0.037 | 0.120 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".