Natural abundance carbon isotope ratio analysis and its application in the study of diet and metabolism
Bibliographic record
Abstract
Due to differences in carbon assimilation pathways between plants, there are subtle but distinct variations in the carbon isotope ratios of foods and animal products throughout the food supply. Although it is well understood that the carbon isotope ratio composition of the diet influences that of the consumers' tissues, the application of natural abundance carbon isotope ratio analysis in nutrition has long been underappreciated. Over the past decade, however, several studies have investigated the utility of carbon isotope ratio analysis for evaluation of nutritional biomarker status, primarily focusing on its application as an objective indicator of sugar and animal protein intake. More recently, research investigating the application of natural abundance measurements has been extended to study fatty acid metabolism and has yielded encouraging results. Collectively, data from large-scale observational studies and experimental animal studies highlight the potential for carbon isotope ratio analysis as an additional and effective tool to study diet and metabolism. The purpose of this review is to provide an overview of natural abundance carbon isotope ratio analysis, its application to studying nutrition, and an update of the research in the field.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".