Bibliographic record
Abstract
Iron deficiency anemia is highly prevalent in developing countries like Pakistan. It is quite predominant in the university community especially among pregnant women. The fetus's and newborn infant's iron status depends on the iron status of the pregnant woman and therefore, iron deficiency in the mother-to-be means that growing fetus probably will be iron deficient as well. Group that is at the highest risk of anemia in society is women in their reproductive years. Multiple reasons such as menstruation, gender discrimination, low socioeconomic status, genetics, lack of proper nutrients and poor medical assistance and access can be blamed for this condition. The outcomes are fatigue, compromised neonatal health, lack of focus and mental disorders. One-fifth women are anemic in Pakistan, says statistics of WHO. Prevalence in ever married women of 15-44 years is 26% in urban and 47% in rural areas, which shows failure of interventions. It is burdening Pakistan's health care systems and economy. People needs to be educated on preventing anemia, identifying its symptoms, treatment and consequences through media, articles campaigns, hospitals and government needs to provide affordable supplements and proper nutritional guide lines to the concerned patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".