Bibliographic record
Abstract
Alzheimer's disease is a major cause of morbidity and mortality. Currently, there are no disease-modifying pharmacotherapies for this condition. Aducanumab, an amyloid beta-directed monoclonal antibody that targets aggregated forms of amyloid-beta in the brains of people with Alzheimer's disease, has raised hopes that such a therapy has been discovered, but its approval by the US Food and Drug Administration has engendered a good deal of controversy. A similar application for approval has been submitted to Health Canada. In response to this, a group of Canadian clinical dementia experts representing a number of organizations, including the Canadian Geriatrics Society, was convened by the Canadian Consortium on Neurodegeneration in Aging (CCNA) to discuss the evidence currently available on this agent and seek consensus on what advice they would offer Health Canada on the application. There was wide-spread agreement that it would be premature for aducanumab to receive approval for the treatment of Alzheimer's disease. It was also noted that the Canadian health-care system is poorly prepared at this time to deal with a disease-modifying therapeutic with targeting, administration, and monitoring characteristics like aducanumab. In this paper, the consensus reached is presented along with its underlying rationale.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.006 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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; both teacher heads agree on what is shown here.
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".