Phenotypic Classification and Clinical Examination of Anemia in Iraqi Water Buffalo in Nasiriyah Governorate
Bibliographic record
Abstract
This research aims to classify anemia cases in the Iraqi water buffalo population by collecting 140 blood samples from buffaloes in Nasiriyah Governorate pastures. These samples were collected randomly from three age groups: > 1 year, 1-4 years, and < 5 years. Blood sample analysis revealed 45 anemia cases (32.12%) and 95 healthy cases (67.88%). Phenotypic classification of anemia encompassed microcytic hypochromic (12.14%), macrocytic hypochromic (7.85%), normocytic hypochromic (6.42%), and normocytic normochromic (5.71%) cases. Erythrocyte sedimentation rate (ESR) notably increased in anemic buffaloes, displaying a statistically significant disparity (P< 0.05) compared to healthy counterparts. Anemia cases exhibited higher neutrophil counts in white blood cell relative differentials. For the three age groups, hemoglobin (Hb), packed blood cell volume (PCV), and total red blood cell count (RBC) values indicated significant decreases from normal levels, showcasing statistical significance (P< 0.05) between healthy and anemic buffaloes. While anemia cases generally displayed normal iron concentrations, microcytic anemia demonstrated lower iron levels in the 1-4 and >5 years age groups, with iron levels reaching the minimum global normal range in the <1 year age group. Copper concentrations remained normal in all healthy cases and anemia cases, except for microcytic anemia, which showed reduced levels across age groups. In conclusion, this study comprehensively characterizes anemia in Iraqi water buffaloes through clinical, hematological, and elemental analyses. The findings underscore the prevalence of various anemia types, their age-related variations, and significant hematological deviations in anemic buffaloes compared to healthy counterparts. This research enhances our understanding of anemias' impact on this population and provides valuable insights for future diagnostic and management strategies.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".