Review: some screening tests for dementia are accurate and practical for use in primary careCommentary
Bibliographic record
Abstract
T Holsinger Correspondence to: Dr T Holsinger, Durham VA Medical Center, Durham, NC, USA; tracey.holsinger@va.gov How accurate are screening tests for detecting dementia in older people in primary care settings? ### Data sources: MEDLINE and PsycINFO (2000 to April 2006). Earlier studies were covered by a previously published review.* ### Study selection and assessment: English-language studies that evaluated screening tests for dementia used by general practitioners in people >60 years of age who did not have clinically obvious dementia. Included studies were required to use an acceptable criterion standard to diagnose dementia. Studies of patients in institutions or with <6 years of education, and those involving diagnostic imaging or laboratory or physiological tests were excluded. 29 studies involving 38 assessments of 25 screening instruments met the selection criteria. Quality of individual studies was assessed based on sample size, participant selection, …
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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 | 0.009 | 0.070 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".