DERIVE – Development of Riboflavin biomarkers to relate dietary sources with status, gene-nutrient Interactions and Validated health Effects in adult cohorts – & VALID – Valerolactones and healthy Ageing: LInking Dietary factors, nutrient biomarkers, metabolic status and inflammation with cognition in older adults
Bibliographic record
Abstract
DERiVE: Sub-optimal riboflavin status may be more widespread than is generally recognised across the developed world, because of the reliance on dietary data only in nutrition surveys, without biomarker evidence. DERIVE will address this gap by developing accessible riboflavin biomarkers for use in population surveys globally, and by demonstrating important functional, gene-nutrient and health effects of optimal riboflavin status in Canadian, Irish and UK cohorts. The proposed study will access bio-banked blood samples (collected under the JINGO initiative http://www.ucd.ie/jingo/) and data from one the most comprehensive dietary surveys in the EU, the Irish National Adult Nutrition Survey (www.iuna.net) as well as bio-banked specimen and data from the BC Generations Project (www.bcgenerationsproject.ca), part of the Canadian Partnership for Tomorrow Project, a major research platform for the study of disease causation. VALID: Polyphenols, particularly procyanidins (abundant in foods such as tea, cocoa, grapes, nuts and berries), may be beneficial in maintaining better cognitive function in ageing, but investigating their role in relation to health is hampered by the lack of robust biomarkers of dietary intake. We will validate novel plasma biomarkers of procyanidin-rich foods and link them with inflammation, metabolic health and cognition in an ageing European population. VALID draws on the TUDA cohort, a unique resource on 5200 adults aged 60-102 years recruited from the UK and Ireland, providing a range of biomarkers and health measures. Apart from performing new analysis on bio-banked TUDA samples, we will access 'TUDA 5+', a follow-up study of 1000 participants from the original cohort 5 years after initial investigation, to determine the role of procyanidin-rich foods in preventing cognitive decline over a 5-year follow-up period.
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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 | 0.015 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.006 |
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".