CAN‐Thumbs UP (Canada)
Bibliographic record
Abstract
Abstract Background The Canadian Consortium on Neurodegeneration in Aging (CCNA) was founded in 2014 to bring together Canada's dementia research community to work together in a more synergistic manner to catalyze new important progress in dementia research in Canada. Teams are funded to work on questions and themes from basic science to clinical work. An important new initiative in Phase 2 of CCNA (2019‐24) is to set up a national study on dementia prevention. CCNA's "Canadian Therapeutic Platform Trial for Multidomain Interventions to Prevent Dementia "(CAN‐Thumbs UP or CTU) has begun with funding from the CIHR (national Canadian research fund) and the Alzheimer Society of Canada. It's building a research program that includes the recruitment of a Trial Ready Cohort (TRC) of over 2,000 non‐demented older individuals at high risk for dementia. These individuals will undergo detailed assessment focusing on cognitive level and risk factors, and be monitored and followed closely over 12 months using instrumentation such as actigraphy and activity monitoring as well as burst cognitive testing. They will also be offered a Brain Health Support Program (BHSP). The BHSP will offer internet‐based weekly modules to encourage lifestyles modification and awareness of dementia risk factors such as hearing loss and diabetes. The BHSP will become the "baseline" of best information on prevention of dementia that should be made available to the population. The initial program will focus on optimizing compliance, and fidelity of the interventions to allow that they reach the broad public with the most opportunity for effective uptake. At the same time, we will be designing a Master Trials Protocol (including a single uniform master protocol, uniform inclusion and exclusion criteria and common outcome measures) which will later be used to carry out combinations of multidomain interventions ‐ both lifestyle and pharmacological ‐ on subset populations of this Trial Ready Cohort. In these intervention trials, we plan to tailor interventions to individuals with specific risk factors (e.g., sleep interventions for those showing fragmented sleep). CAN‐Thumbs UP is still in its early stages, and is being built in conversation with scientists from WW Finger.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.542 | 0.115 |
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".