Shared lunch intake: implications of food sharing in double fortified salt intervention trial (804.30)
Bibliographic record
Abstract
Shared lunch intake: implications of food sharing in double fortified salt intervention trial Sudha Venkatramanan 1 , Grace S. Marquis 1 , Jere D. Haas 2 1 McGill University, Canada, 2 Cornell University, NY Treatment contamination can be a challenge in randomized control trials. Sharing foods during lunch is a common social practice in the tea garden culture and it has a significant role in creating a communal bond. The objective of this analysis was to assess the amount of treatment that was diluted due to contamination. The double masked study randomized 248 women to either double fortified salt (DFS) or iodized salt (control) for 10 mo. Information on the amount of food shared between the women in two different ethnic groups and total amount consumed was measured by weighing the lunch intake. The women were 18‐55 y old, Adivasi or Nepali, not pregnant or lactating, and full‐time experienced tea pickers. The endline lunch intake data from 206 women was used to estimate the amount of treatment received from sharing and the effect of treatment on the energy and nutrient intakes at lunch. Average shared foods received from other members and given away to others were 91.6 and 93.6 g, respectively. Food sharing resulted in both the control and treatment groups benefitting from DFS. The proportion of treatment received through the lunch by the IS and DFS groups were 40% and 54 %, respectively. A significant association of ethnicity ( P <0.0001) on the total food and macronutrient intakes at lunch was observed. The results conclude that sharing lunches resulted in the contamination of the control group, somewhat diminishing the expected group difference in iron intake. Grant Funding Source : Supported by the Mathile Institute for the Advancement of Human Nutrition and the Micronutrient Init
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".