Normative data for the Montreal Cognitive Assessment (MoCA) in a population-based sample
Bibliographic record
Abstract
Dr. Holloway's reflection of removing the ventilator from a patient with terminal amyotrophic lateral sclerosis (ALS) was touching and thoughtful. 1 Patients with ALS, faced with their mortality and knowing there is no hope of ameliorating their disease, often wrestle with the meaning of life.Frequently, as in Holloway's patient, they meet the challenge with bravery and courage and, in the process, have a profound impact on their physicians.Holloway's story reminded me of one of my patients with ALS.For the past few years, his severe speech disturbance has prevented any coherent verbal communication; he barely swallows; and has no use of his arms.He is totally dependent on his wife for all his daily activities.Yet, as an avid football fan, he dutifully trudges down and up the stadium steps of Mountaineer Field on fall weekends, his paralyzed arms hanging loosely at his side, and spends weeks in Florida during his father's winter fishing trip.We sit near each other at the games and he always has a cheerful greeting for me.He has taught me that life can be fun and fulfilling even when there's so much you cannot do.
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 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 | 0.003 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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; 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".