Retrospective review of diagnostic performance of intracranial translucency in detection of open spina bifida at the 11–13‐week scan
Bibliographic record
Abstract
OBJECTIVES: To evaluate diagnostic performance of intracranial translucency (IT) for detection of open spina bifida and interobserver agreement for visualization of IT during the 11-13-week scan. METHODS: A retrospective study was undertaken in a tertiary referral center. Two hundred 11-13-week scans for nuchal translucency, performed by sonographers certified by The Fetal Medicine Foundation, U.K., were reviewed independently for IT by two expert observers. When IT was not seen, the observers determined whether this was due to poor IT image quality or the presence of spina bifida. Discordant cases were reviewed by a third observer and the majority decision was used for analysis. All observers were blinded to individual pregnancy outcome and the number of cases with spina bifida. RESULTS: There were 191 normal fetuses, eight fetuses with open spina bifida and one with closed spina bifida (this case was excluded from analysis). IT was seen in 150 fetuses and all were normal. In six of the 49 cases in which IT was not seen, IT non-visibility was attributed to open spina bifida; among these cases, four fetuses had open spina bifida and two were normal. In the remaining 43 cases (including 39 normal fetuses), IT non-visibility was attributed to inadequate image quality. Sensitivity was 50% (4/8) and specificity was 99% (150/152). Concordance between the two observers concerning IT visibility was 79%, (κ = 0.47, representing moderate agreement). CONCLUSION: There was moderate interobserver agreement for visualization of IT on images obtained for nuchal translucency measurement at 11-13 weeks. When IT was confidently seen, open spina bifida could be excluded. However, non-visibility of IT correctly diagnosed only 50% of fetuses with open spina bifida.
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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 | 0.006 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".