Editorial: Advances in Understanding Alzheimer's Disease, and the Contributions of Current Alzheimer Research: Ten Years on and Beyond
Bibliographic record
Abstract
The initial issue of Current Alzheimer Research (CAR) was first published in 2004, a year marked by the glories of the Athens Summer Olympics as well as the destruction of the Asian Tsunami[1]. Over the last decade, scientific knowledgehas moved rapidly forward across numerous disciplines,marked by the discovery of the potential for water and life on Mars [2,3], the generation of the first induced pluripotent stem cells [4], the creation of the first cell controlled by a synthetic genome [5], and genome editing [6].In the realm of dementia -now, beyond the centennial of the first presentation by Alois Alzheimer on the disease that bears his name [7]–important changes too have occurred in the past decade. Whereas the exact prevalence of dementia remains unknown, it is crystal clear that dementia is a common, devastating and costly condition amongst the elderly. The WHO 2012 Report “Dementia: a public health priority” [8] estimatesthat 35.6 million people suffered with dementia worldwide in 2010. An estimated incidence that is much higher than that approximatedin 2004 (18 million people [9]),and this value has undoubtedly grown still more in 2014.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.012 | 0.015 |
| Insufficient payload (model declined to judge) | 0.025 | 0.021 |
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".