V. A. Kral and the origins of benign senescent forgetfulness and mild cognitive impairment
Bibliographic record
Abstract
BACKGROUND: The concept of benign senescent forgetfulness (BSF) was introduced in 1958 by V. A. Kral, consultant neuropsychiatrist to the Montreal Hebrew Old People's and Sheltering Home (hereafter the Home). BSF was criticized and mild cognitive impairment (MCI) was adopted years later. In this paper I argue that a notion of MCI also originated with Kral. METHODS: A historical review was undertaken of the Canadian Jewish Congress archives in Montreal, Kral's biography and his publications, as well as relevant literature. A discussion was held with one of Kral's collaborators. RESULTS: In the mid-1950s the administration of the Home sought research-derived recommendations to improve residents' conditions. In an initial survey, based on a meticulous neuropsychiatric examination, Kral departed from contemporaneous psychiatric nosology and suggested other criteria in order to classify the home's population. He classified one of the five groups, consisting of subjects with mild memory dysfunction, as having BSF. In his next survey, Kral included psychological tests in addition to clinical assessment and focused on the elderly people who were well preserved (good personal and social functioning). This sample was subdivided into four subgroups, including BSF and incipient amnestic syndrome (IAS). The findings revealed: well-preserved aged people; normal (dull) level of general intelligence; subnormal performance of specific memory and perceptual/organization tests; and no significant signs of malignant amnestic syndrome. This construct is very similar to that of MCI, which is widely used today. CONCLUSIONS: The interaction between Kral and a particular home for the elderly at a particular moment in its history gave rise to the concept of BSF, and a notion of what we now call MCI emerged.
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 | 0.001 | 0.003 |
| 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 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".