The Consortium for the early identification of Alzheimer's disease–Quebec (CIMA‐Q)
Bibliographic record
Abstract
Abstract Introduction The Consortium for the early identification of Alzheimer's disease–Quebec (CIMA‐Q) created a research infrastructure to recruit, characterize, and track disease progression in individuals at risk of dementia. Methods CIMA‐Q established standardized clinical, neuropsychological, neuroimaging, blood (plasma, serum, RNA, genomic DNA), cryopreserved peripheral blood mononuclear cells, and cerebrospinal fluid collection protocols. These data and biological materials are available to the research community. Results In phase 1, 115 persons with subjective cognitive decline, 88 with mild cognitive impairment, 31 with early probable Alzheimer's disease, and 56 older adults with no worries nor impairments received detailed clinical and cognitive evaluations as well as blood and peripheral blood mononuclear cells collections. Among them, 142 underwent magnetic resonance imaging, 29 a 18fluorodeoxyglucose positron emission tomography, and 60 a lumbar puncture. Discussion CIMA‐Q provides procedures and resources to identify early biomarkers and novel therapeutic targets, and holds promise for detecting cognitive decline in Alzheimer's disease.
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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 | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".