Bibliographic record
Abstract
Background We present an eighth year experience (1991–98) of ultrasonography in a private office, using a portable ultrasound unit, Aloca SSD‐500. Method Each pregnant woman underwent transvaginal ultrasound examination 7–8w in order to date pregnancy, to confirm fetal viability and the number of fetuses. At 17 weeks, a second trimester screening for Down syndrome was ordered by using BPD, maternal age and maternal serum AFP and free β‐HCG. Later, at 20–22w a detailed scan was performed to all pregnant women in order to exclude fetal anomalies. Results In 1019 consecutive pregnant women, 22 could not recall the date of their LMP and 59 had irregular cycles. By measuring the CRL, the expected date of delivery was accurately calculated. One hundred and seventy‐six women underwent amniocentesis with no complications, and from these, there was only 1 case with trisomy 18. All pregnant women had level II scan. There were 5 cases with abnormalities (1 cystic hygroma, 1 diaphragmatic hernia, 1 with talipes, 1 anencephalic and two with hydrops). We couldn't diagnose prenataly 1 case with coarctation of the aorta, 1 anorectal atresia, 1 microcephaly and 3 with Down Syndrome. All the other women delivered babies with normal anatomy. As far as the cost is concerned, there was no extra charge for ultrasound examinations. Conclusion Office ultrasonography is feasible after long‐term training and experience. Acknowledgements W. R. Lees and J. C. Hobbins.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".