Bibliographic record
Abstract
Blood group genotyping using DNA extracted from fetal tissue is useful to identify fetuses at risk for hemolytic disease of the fetus and newborn (HDFN) due to maternal red cell alloantibodies. Four considerations are important for fetal blood group genotyping. First, paternal heterozygosity must be established, including tests that evaluate RHD hemizygosity. Second, the source of fetal tissue for DNA extraction requires certain considerations. Third, because the fetal genotype is used to predict the expressed phenotype, a thorough knowledge of blood group genetics is required. Moreover, the test algorithm should include the evaluation of the parental phenotypes and genotypes to help identify variant alleles. Fourth, the blood group antigen expression at birth should be evaluated to confirm the inheritance. The identification of an antigen-negative fetus on the basis of the blood group genotype provides significant advantages in managing the pregnancy at risk for HDFN. In the near future, fetal DNA in maternal plasma will likely replace fetal blood group genotyping for RHD. Significant challenges remain to detect other clinically significant blood group antigens using maternal plasma DNA.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 teacher head, 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".