Iron Deficiency Anemia in Growing Years and its Effect on Cognition: A Review
Bibliographic record
Abstract
Iron deficiency anemia is a widespread nutritional problem. Children are particularly vulnerable due to poor maternal iron status and inadequate diet. Since iron plays a vital role in neurological development, its deficiency in early life can lead to altered cognition and motor development. Severe iron deficiency during infancy can affect the major processes such as myelination, development of neurotransmitter pathways, neural metabolism and neural plasticity. The present review intends to provide information on the various effects of iron deficiency during different stages of life cycle. Clinical trials conducted on both humans and animals have established that infants who suffer iron deficiency during the early years of life are known to be under risk for experiencing the long lasting effect of early iron deficiency in future years also. Follow-up studies conducted on infants showed that the anemic children continued to exhibit lower cognitive development compared to their non-anemic counterparts and also had difficulty in the development of motor control tasks. Hence, there is a need to identify and correct iron deficiency anemia during the early years of life to prevent possible future complications.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".