Study of the Association between the Incidences of Congenital Anomalies and Hydrocephalus in Sudanese Fetuses
Bibliographic record
Abstract
This study was designed with an aim to detect the congenital anomalies appear to be linked to and in conjunction with hydrocephalus fetuses in Sudan, when ultrasound is used to exam fetuses in the second and third trimesters of pregnancy. This prospective cohort study was performed from December 2011 to December 2013, in a group consists of 5000 single gestation pregnant Sudanese women. In all cases, maternal ages were 35 years up to 48 years; mean age of 42.5 years. Pelvic; obstetric ultrasound scanning protocol used should meet the standards established by the American Institute of Ultrasound in Medicine (AIUM) for scanning in the second and third trimesters of pregnancy. Statistical Package for the Social Sciences (SPSS) was used to analyze the results. Diagnosed hydrocephalus cases (0.4%) were found to be associated with other fetal anomalies as aqueduct stenosis (45%), spina bifida (30%), Arnold-Chiari malformation (20%) and Dandy-Walker malformation (5%). The incidence of congenital anomalies and hydrocephalus in Sudanese fetuses showed considerable variation among different regions of Sudan. Hydrocephalus is associated with certain congenital anomalies. In agreement with previous studies, hydrocephalus is predominantly in male rather than female fetuses. The prevalence of fetal anomalies and hydrocephalus are within previously reported ranges.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".