Inter‐ and Intra‐Laboratory Variability of Glycemic and Insulinemic Indexes
Bibliographic record
Abstract
Objectives The glycemic index (GI) concept was developed by Jenkins et al in 1981 to classify the glycemic impact of carbohydrate (CHO)‐containing foods. This study aimed at quantifying inter‐ and intra‐laboratory variability on GI, Insulin Index (II), glycemic and insulinemic responses after standardising the protocols in 3 different labs. Methods At least 15 healthy young normal weight subjects with HOMA‐IR < 1.7 were recruited by each lab. They underwent 9 sessions to test a glucose solution (3 times) or 6 different cereal products. The 3 selected labs used the validated GI method (ISO method 26642:2010). Insulin assay and subject selection criteria were standardised. Results GI values for the 6 different products (mean ± SEM) ranged from 44 ± 4 to 92 ± 8. For a same product, the between‐labs differences range was 0 ‐ 11. No lab effect but significant product effects were observed for GI and iAUC glycemia. II values of the 6 different products ranged between 54 ± 3 and 85 ± 9. For a same product, the between‐labs differences range was 0 ‐ 21. Significant lab * product interaction effect was observed for II on 1 product. iAUC insulinemia displayed both significant lab and product effects. Inter‐individual and intra‐individual coefficient of variability (CV) ranges were 20 ‐ 28 % and 18 ‐ 30%, respectively for iAUC glycemia and 35 ‐ 51 % and 22 ‐ 43 %, respectively for iAUC insulinemia. Conclusion No significant lab effect and good product discrimination was observed on GI. Insulin parameters display statistically significant differences between the labs showing the difficulty to compare the results on these parameters.
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 | 0.012 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".