Reference Value Profile for Healthy Individuals From the Aljouf region of Saudi Arabia
Bibliographic record
Abstract
BACKGROUND: Many factors influence hematological values such as sex, age, ethnic origin, geographic location, season, and genetic disease. The aim of this study was to detect the hematological reference value profile for healthy adults from the Aljouf region of Saudi Arabia. METHODS: The project was carried out on 2,040 healthy individuals, 1,152 males and 888 females, with ages ranging from 17 to 28 years. A group of participants were recruited from the higher secondary schools, university students and premarital centers of Aljouf cities. Hematological reference value profile, hemoglobin (Hb) concentration, red blood cell (RBC) count, RBC indices, white blood cell (WBC) count, differential WBC and platelet (Plt) count were measured. Moreover, a peripheral blood film was prepared in order to detect abnormalities of RBC and all samples were examined for liver function tests (LFTs) and renal function test (RFT) performed, along with a lipid profile. RESULTS: Hb concentration, hematocrit (Hct) and RBCs were found to be significantly higher in males than in females (P < 0.01). On the contrary, Plt ranges were significantly lower in male as compared to female (P < 0.01). No significant differences in the study population were determined in the other hematological parameters (P > 0.05). CONCLUSION: Our findings reflect that healthy adults from the Aljouf region have some hematological parameters differing quantitatively from Caucasians. The hematological reference value profile reported here can be used as normal reference values for Saudi people of the Aljouf region to help in diagnosis and consequently treatment of individuals with hematological disorders.
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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 | 0.000 |
| 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) | 0.001 | 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".