A Coumarin-Based Array for the Discrimination of Amyloids
Bibliographic record
Abstract
Self-assembly of misfolded proteins can lead to the formation of amyloids, which are implicated in the onset of many pathologies including Alzheimer's disease and Parkinson's disease. The facile detection and discrimination of different amyloids are crucial for early diagnosis of amyloid-related pathologies. Here, we report the development of a fluorescent coumarin-based two-sensor array that is able to correctly discriminate between four different amyloids implicated in amyloid-related pathologies with 100% classification. The array was also applied to mouse models of Alzheimer's disease and was able to discriminate between samples from mice corresponding to early (6 months) and advanced (12 months) stages of Alzheimer's disease. Finally, the flexibility of the array was assessed by expanding the analytes to include functional amyloids. The same two-sensor array was able to correctly discriminate between eight different disease-associated and functional amyloids with 100% classification.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".