Corrigendum to “Dietary patterns, inflammatory biomarkers and cognition in older adults: An analysis of three population-based cohorts” [Clin Nutr 10 (43) (2024) 2336-2343]
Bibliographic record
Abstract
The authors regret to announce the following changes to the manuscript, which do not affect the results presented in the main manuscript: 1. Keywords: diet; cognition; inflammation; reduced rank regression; CLSA 2. Disclaimer The opinions expressed in this manuscript are the author's own and do not reflect the views of the Canadian Longitudinal Study on Aging. 3. A mention in the Acknowledgements to the team collecting dietary data: The development, testing and validation of the Short Diet Questionnaire (SDQ) were carried out among NuAge study participants as part of the Canadian Longitudinal Study on Aging (CLSA) Phase II validation studies, CIHR 2006–2008. The NuAge study was supported by the Canadian Institutes for Health Research (CIHR), Grant number MOP-62842, and the Quebec Network for Research on Aging, a network funded by the Fonds de Recherche du Québec-Santé. 4. We add four references related to cognitive test measures and to the Short Food Frequency Questionnaire in CLSA in the following sentences: Executive function and processing speed were assessed with the Stroop test in all three cohorts (1–3). The MAT consists of an alternating series of numbers and letters and demands timed performance and category-switching assessing executive function. It is a valid screening tool with good discriminative power to detect cognitive impairment (4, 5). [...] and CLSA used a 36-item a qualitative FFQ (6). The authors would like to apologise for any inconvenience caused. References 1. Stroop JR. Studies of interference in serial verbal reactions. Journal of Experimental Psychology. 1935;18(6):643-62. 2. Bayard S, Erkes J, Moroni C. Victoria Stroop Test: Normative Data in a Sample Group of Older People and the Study of Their Clinical Applications in the Assessment of Inhibition in Alzheimer's Disease. Archives of Clinical Neuropsychology. 2011;26(7):653-61. 3. Troyer AK, Leach L, Strauss E. Aging and Response Inhibition: Normative Data for the Victoria Stroop Test. Aging, Neuropsychology, and Cognition. 2006;13(1):20–35. 4. Salib E, McCarthy J. Mental Alternation Test (MAT): a rapid and valid screening tool for dementia in primary care. International Journal of Geriatric Psychiatry. 2002;17(12):1157-61. 5. Teng E. The Mental Alternations Test (MAT). The Clinical Neuropsychologist. 1995;9(3):287. 6. Shatenstein B, Payette H. Evaluation of the Relative Validity of the Short Diet Questionnaire for Assessing Usual Consumption Frequencies of Selected Nutrients and Foods. Nutrients. 2015;7(8):6362-74.
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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 | 0.005 | 0.041 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.009 | 0.010 |
| Insufficient payload (model declined to judge) | 0.072 | 0.048 |
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".