[Prenatal diagnosis of cleft palate by 3D ultrasound].
Bibliographic record
Abstract
A case of a fetus seen at 33.2 weeks of gestation who was diagnosed with cleft lip in the third quarter by routine ultrasound. Describes the sequential steps that led to a multidisciplinary support the diagnosis of cleft palate by three-dimensional image reconstruction, which were originally obtained to demonstrate the fetal face surface. Birth confirmed the prenatal findings and established the diagnosis of cleft lip and cleft hard and soft palate. It has been reported that the diagnosis of facial clefts can be done with relative ease prenatally, but the detection rate of facial clefts in routine tests is only 20%. Until recently the diagnosis of cleft palate is not considered possible, however in recent years advances in three-dimensional technology has made possible the development of techniques for the assessment of the palate and various authors have reported promising results of ingenious applications that make think that in the near future will approach the palate a fact. We discuss the advantages and disadvantages of these methods are relatively new and highlights how valuable this information is for parents of the affected creature.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".