Modeling <sup>13</sup>C Breath Curves to Determine Site and Extent of Starch Digestion and Fermentation in Infants
Bibliographic record
Abstract
ABSTRACT Background The colon salvages energy from starch, especially when the capacity of the small intestine to digest it is limited. The aim of this study was to determine the site and relative extent of starch digestion and fermentation in infants. Methods Thirteen infants (10 male and 3 female infants), median age 11.8 months (range, 7.6–22.7 months), were fed a starchy breakfast containing 13C‐labeled wheat flour after an overnight fast. Duplicate breath samples were obtained before breakfast and every 30 minutes for 12 hours. Breath 13CO2 enrichment was measured using isotope ratio mass spectrometry, and results were expressed as percentage dose recovered (PDR) for each 30 minutes. The PDR data were analyzed and mathematically modeled assuming either a constant estimate of CO2 production rate or adjusted for physical activity. Results Mean ± SD cumulative 13C PDR (cPDR) at 12 hours was 21.3% ± 8.4% for unadjusted data and 26.5% ± 11.6% for adjusted data. A composite model of two curves fit significantly better than a single curve. Modeling allowed estimation of cPDRs of small intestine (17.5% ± 6.5% and 22.7% ± 9.3% for unadjusted and adjusted data, respectively) and colon (4.6% ± 2.9% and 6.3% ± 5.4%). Conclusions Modeling of 13CO2 enrichment curves after ingestion of 13C‐enriched wheat flour is an attractive means to estimate the contribution of the upper and lower gut to starch digestion and fermentation.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".