Risk factors for anemia among adolescent girls
Bibliographic record
Abstract
Introduction Adolescence is a crucial period of growth and development in girls and boys. During this period the risk of iron deficiency and anemia appears. In India iron deficiency anemia is a major public health problem affecting people from all walks of life (Dallman, Simes & Stekel, 1980). Objective to explore the factors influencing anemia among anemic adolescent girls. Design a qualitative analysis using grounded theory was carried out for the present study. Setting homes of the selected adolescent girls. Instruments a questionnaire on background information, record of investigations, nutritional assessment and a semi structured questionnaire for interviewing. Participants ten adolescent girls purposively selected; participated in the present study Results the age of the adolescent girls ranged from 12 to 15 years. They were studying in 8th, 9th or 10th standard. Calorie, iron & protein consumption was less compared to their requirement. Hemoglobin ranged from 7.2 to 8.2 gm/ dl.Conclusion adolescents perceived anemia as a major problem. Menstruation, worm infestation and dietary deficiency were found as the major cause; which was consistent with the literature. Therefore the study helps to conclude that health awareness programme for the adolescent girls and their society is essential in preventing anemia
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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) | 0.004 | 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".