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Prevalence and molecular characterization of abnormal hemoglobin in eastern Guangdong of southern China

2011· article· en· W2067521894 on OpenAlexaboutno aff
Min Lin, Qiang Wang, Lei Zheng, Yue Huang, Fen Lin, C Dal Lin, Liying Yang

Bibliographic record

VenueClinical Genetics · 2011
Typearticle
Languageen
FieldMedicine
TopicHemoglobinopathies and Related Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsHemoglobinGenotypeHemoglobin variantsThalassemiaIncidence (geometry)Molecular epidemiologyBiologyMedicineGeneticsInternal medicineGene

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.285

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.027
GPT teacher head0.287
Teacher spread0.260 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations42
Published2011
Admission routes1
Has abstractyes

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