P65Feasibility and accuracy of NT measurement in twin pregnancies
Bibliographic record
Abstract
Background The aim of our study was to evaluate the feasibility and accuracy of nuchal translucency measurement (NT) in twin pregnancies. Method We reviewed nt images of 66 pairs of twins (10.3–14 weeks gestation), matched with nt images of 66 pairs of consequent singleton pregnancies with similar gestational ages. Each of the inspected images was assigned a score, which classified it into one of four quality zones. Results In the twins, as well as in the singleton control group, the vast majority of the nt images were in the excellent‐reasonable zones (−88%), and 10% in each of the groups had their nt images in the intermediate zone (11% vs. 12%). Less than 1.5% of the images were of unsatisfactory quality (1.5% vs. 0.8%), according to the strict criteria, required for reliable, comparable and reproducible results. (Hennan et al. Ultrasound Obstet Gynecol 1998; 12: 398–403). Conclusion NT measurement in twin pregnancies is as feasible, accurate and reproducible as in singleton pregnancies. However, it provides a better DS risk assessment when compared with the second trimester triple test in twin pregnancies, as it evaluates DS risk individually for each of the fetuses.
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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 | 0.004 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".