Diarrhea and Novel Dietary Factors Emerge as Predictors of Serum Vitamin B <sub>12</sub> in Panamanian Children
Bibliographic record
Abstract
BACKGROUND: The role of gastrointestinal infection as a factor determining vitamin B12 status in populations with low intake of animal-source foods is unclear. OBJECTIVE: To determine dietary adequacy and serum concentrations of vitamin B12 in an extremely impoverished indigenous population of Panamanian children aged 12 to 60 months, and to identify predictors of both dietary and serum vitamin B12. METHODS: A previous community-based survey provided the usual dietary intake and personal, household, and infection (Ascaris and diarrheal disease) information for 209 weaned children. Serum vitamin B12 was assayed using electrochemiluminescence for 65 of these children. Children with adequate or inadequate dietary vitamin B12 intake were compared, and predictors of dietary and serum vitamin B12 were identified using stepwise regression analyses of one index child per household. RESULTS: Dietary vitamin B12 intake was inadequate in 43% of children; these children were poorer, had less frequent diarrhea, and obtained a higher percentage of their energy from carbohydrate than children with adequate intake. Energy intake positively predicted dietary vitamin B12 intake. In contrast, serum vitamin B12 concentrations were normal in all but 3% of the children. Serum vitamin B12 was positively associated with weekly servings of fruit, corn-based food, and name (a traditional starchy food), but not with animal-source foods. Finally, serum vitamin B12 was not associated with Ascaris intensity but was lowered with increasing frequency of diarrhea. CONCLUSIONS: Although inadequate dietary intake of vitamin B12 was common, most serum values were normal. Nevertheless, diarrheal disease emerged as a negative predictor of serum vitamin B12 concentration.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".