Identification of six new <i>RHCE</i> variant alleles in individuals of diverse racial origin
Bibliographic record
Abstract
BACKGROUND: The introduction of molecular methods into routine blood typing is prompting the identification of new blood group alleles. Discrepancies between the results of genotyping and serology or chance events uncovered during genotyping prompted additional investigations, which revealed six new RHCE variant alleles. STUDY DESIGN AND METHODS: Samples from eight blood donors, two patients (one prenatal), and a patient's relative, all of diverse racial origin, were analyzed by standard serology methods, targeted genotyping arrays, DNA sequencing, and allele-specific polymerase chain reaction. RESULTS: Six new RHCE alleles were identified, namely, RHCE*cE84A, RHCE*ce202G, RHCE*ce307T, RHCE*Ce377G, RHCE*ce697G,712G,733G,744C, and RHCE*Ce733G. CONCLUSION: While implementation of new assays in commercial genotyping platforms to detect the polymorphisms reported here may not be justified given their apparent rarity, software interpretative algorithms may benefit from the identification of new alleles for a more accurate determination of genotypes and prediction of phenotypes.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".