Age‐related cognitive impairments in domestic cats naturally infected with feline immunodeficiency virus
Bibliographic record
Abstract
Abstract Background Age‐related dementia has been documented in domestic cats; however, its interaction with naturally occurring feline immunodeficiency virus (FIV) infection has been investigated minimally. Methods Visuospatial working memory (VSWM) and problem‐solving (PS) ability were evaluated in FIV‐infected ( n = 37) and control cats ( n = 39) using two cognitive tasks tested serially, which assessed the ability of cats to remember the location of a baited container after a set delay, then evaluated the capability of the cats to manipulate the container to obtain the food within a time limit. Cats were categorized using 7 years of age as a cut‐off to determine age‐related differences. The relationship between cognitive performance and FIV viral load was investigated using real‐time PCR cycle threshold (C t ) values. Results Age significantly affected VSWM and PS ability. Younger cats had better VSWM performance and PS ability compared to older cats with the same FIV status. There was no difference between younger FIV‐positive and negative cats in either part of the task. While older FIV‐positive cats had significantly worse VSWM than older FIV‐negative cats, no differences were found in PS ability. Additionally, C t values predicted VSWM but not PS ability. Conclusion Age‐related cognitive impairments and FIV infection appear synergetic, causing greater cognitive deficits in older FIV‐infected cats.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".