Brief Continuous Recognition Task for Early Alzheimer Detection and Tracking
Bibliographic record
Abstract
Abstract Background Alzheimer’s Disease (AD) affects memory processing in the brain. An important aspect of AD assessment and study is memory testing, which can be done with excellent efficiency using a Continuous Recognition Test (CRT). A CRT was designed for online administration to provide 25 unique, complex, interesting images, which were initially presented for up to 3 seconds, and 25 repeated images, which required a response to indicate recognition (takes about 90 seconds). The images include 5 from each of 5 categories, from a set of 3,000 images, ensuring that a broad spectrum of memory is interrogated. The selected images are culturally neutral, and the instructions are provided in 120 languages, so the test is comparable across most countries, and performance is not affected by racial, cultural, or ethnic variations. The test is engaging and has been taken by many individuals over 100 times and by several individuals over 1,000 times. Two studies have compared this test with the Montreal Cognitive Assessment (MoCA) (in China and Netherlands) and found that this test performed at least as well. Method Data was examined from over a million CRT administrations from 3 sources: at the URL: www.memtrax.com, including over 18,000 unique users recruited by a French company (HAPPYneuron, INC), over 200,000 unique users from free access, and over 90,000 unique users from a free recruitment program (www.brainhealthregistry.org, part of the Alzheimer’s Disease Neuroimaging Initiative). Response time data was available for every image of each CRT, and the 3 populations were evaluated for HITs (correct recognitions), Correct Rejections (CRs, not responding to a new image), and response time to HITs (RT), including average RTs. Result Analyses indicated that 97% of individuals, across sites who scored better than chance (65% correct), performed better than 80% correct. Percent HITs and CRs and RTs showed a dichotomy with HITs (recognitions) correlating with RT (an AD dysfunction), while a separate group had fewer correct rejections (response disinhibition) and RT inconsistency, presumably related to fronto‐temporal dementia (clinical observation). Statistical analysis provides precision of impairment estimation. Conclusion A CRT can be used for early AD screening, memory assessment, and progression tracking.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.007 |
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".