Diagnosis and Treatment of Dementia: the Fourth Canadian Consensus Conference
Bibliographic record
Abstract
It is inevitable that when discoveries are made in any medical fi eld there is pressure to move expeditiously to clinical applications of these discoveries. While there is every reason to disseminate widely the results of effi cacious therapeutic trials that improve meaningful clinical outcomes, and diagnostic strategies that are more sensitive, more specifi c, less burdensome to the patient and more parsimonious of resources, some restraint is advisable when the benefi ts are less compelling. For example, a technique that allows an earlier diagnosis of an incurable disease – such as Alzheimer’s disease (AD) – risks labeling an individual, aff ecting the person’s ability to acquire life, health or travel insurance, and may result in suspension of driving privileges. Finding the balance between embracing leading-edge technologies prematurely and failing to accept proven therapies or diagnostic strategies in a timely manner is the sweet spot to which we should all aspire. We must try to avoid repeating the unfortunate experiences occasioned by widespread prescription of medications before the true range of adverse eff ects has been elucidated (for example, rofecoxib), by surgical procedures of dubious value (for example, external carotid artery to internal
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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 teacher head, 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".