Economic and demographic predictors of dietary variation and nutritional indicators in Nicaragua
Bibliographic record
Abstract
Abstract Objectives We measured carbon and nitrogen isotopic ratios in a contemporary population, and tested how the isotopic variability relates to measures of socioeconomic status (e.g., household wealth) and anthropometric measures (e.g., standardized height‐for‐age and weight‐for‐age z ‐scores). Methods Hair samples from individuals living in the Bosawas Biosphere Reserve in Nicaragua were analyzed for δ 13 C and δ 15 N, and these data were examined in relation to individual (e.g., age, sex, anthropometrics) and household (e.g., household size, wealth) variables. Results We found through mixed‐effects modeling that δ 13 C and δ 15 N varied predictably with individual age and household wealth. δ 13 C and δ 15 N did not, however, improve models predicting variation in individual anthropometric measures. Conclusion These results indicate that, although there is a relationship between diet (δ 13 C and δ 15 N) and socioeconomic variables, these dietary differences are not the main cause of health differences in this population.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".