Improvements in perceptual and cognitive performance linked to baseline iron status and consumption of a double‐fortified salt
Bibliographic record
Abstract
Iron deficiency (ID) has numerous effects on individual functioning, including perception and cognition. Research has documented substantial deficits with ID and improvements with iron repletion. However, a weakness of this work has been its lack of specificity in measuring these changes. The present study considered the effects of ID and repletion in 248 female tea‐pickers of reproductive age (18–55 y) in West Bengal, India. Six measures of perceptual and cognitive performance‐‐‐simple reaction time, 2 measures of visual detection, 2 measures of attention, and recognition memory‐‐‐were selected for their ability to selectively examine perceptual and cognitive functioning relative to iron status. The measures were used in a randomized controlled double‐blind intervention involving salt double‐fortified with iodine and iron (DFS). Measures were taken before and after a 10‐month intervention. We previously reported substantial improvements as a function of experimental condition. We here link improvements in specific aspects of perceptual and cognitive performance to baseline iron status and total amount of DFS consumed. Support: Mathile Institute, Micronutrient Initiative, and NSF.
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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 | 0.000 | 0.000 |
| 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) | 0.003 | 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".