Prevalence and molecular characterization of abnormal hemoglobin in eastern Guangdong of southern China
Bibliographic record
Abstract
Abnormal hemoglobins (Hbs) are the most commonly inherited disorders in humans. Their frequency and types change considerably with geographic location and ethnic group. To investigate the molecular epidemiological characterization of abnormal Hbs in eastern Guangdong of southern China, a total of 11,450 'healthy' subjects were subjected to hemoglobin electrophoresis screening. Samples of EDTA-K(2) blood with abnormal Hbs were analyzed by CELL-DYN1700 blood analyzer; thalassemia genotypes and Hb E variant were identified by gap-PCR and/or reverse dot blot (RDB). The genotypes of Hb variants were detected by PCR and sequencing. The incidence of abnormal Hbs was 0.358%(41/11,450) in Chaozhou, including 12.2% (5/41) Hb J, 4.9% (2/41) Hb K, 9.7% (4/41) Hb Q, 31.7% (13/41) Hb G/D and 41.5% (17/41) Hb E. Eight types of Hb variants were found, including 3 cases of Hb J-Bangkok, 2 cases of Hb J-Wenchang-Wuming, 2 cases of Hb New York, 4 cases of Hb Q-Thailand, 5 cases of Hb G-Waimanalo, 4 cases of Hb Ottawa, 4 cases of Hb G-Chinese and 17 cases of Hb E. In comparison with other areas of Guangdong, Chaozhou had a different pattern of abnormal Hbs with a high prevalence of Hb G/D. This study describes the prevalence and molecular characterization of abnormal Hbs in eastern Guangdong.
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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".