Progress in Clinical Neurosciences: Canadian Guidelines for the Development of Antidementia Therapies: A Conceptual Summary
Bibliographic record
Abstract
The magnitude of the problems faced by an aging Canadian society has been clearly identified. Perhaps the single most important problem is the increasing incidence of dementia. Alzheimer's disease (AD) accounts for 50-60% of the dementias in later life within a spectrum of other contributing dementias. Regulatory approval has been given to Acetylcholinesterase inhibitors for the symptomatic treatment of mild to moderate AD, and conditional approval to memantine for the symptoms of moderate to severe AD. There has been no regulatory approval for the treatment of the degenerative dementias beyond AD. The very rapid progress in the past decade in biotechnology and in the molecular biology of the dementias is supporting a new generation of innovative treatment strategies that will more directly target the underlying disease pathogenic mechanisms. Such treatments will foreseeably include immunotherapies, anti-aggregants that may prevent misfolding and deposition of proteins, and neuroregenerative interventions. These Guidelines follow the 2nd Canadian Conference on the Development of Antidementia Therapies, held in 2004, which covered a range of design, methodological and ethical issues facing clinical researchers and regulatory authorities. They are intended to provide a common point of reference and guidance in Canada for therapeutic development of the dementias.
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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 | 0.014 | 0.012 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.018 | 0.025 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.007 | 0.003 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.007 | 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".