Schinzel–Giedion syndrome: Report of splenopancreatic fusion and proposed diagnostic criteria
Bibliographic record
Abstract
We report on the 46th patient with Schinzel-Giedion syndrome (SGS) and the first observation of splenopancreatic fusion in this syndrome. In the antenatal period, a male fetus was found to have bilateral hydronephrosis. Postnatally, in keeping with a diagnosis of SGS, there were large fontanelles, ocular hypertelorism, a wide, broad forehead, midface retraction, a short, upturned nose, macroglossia, and a short neck. Other anomalies included cardiac defects, widened and dense long bone cortices, cerebral ventriculomegaly, and abnormal fundi. Splenopancreatic fusion, usually encountered in trisomy 13, was found on autopsy. Schinzel-Giedion syndrome is likely a monogenic condition for which neither the heritability pattern nor pathogenesis has yet been determined. A clinical diagnosis may be made by identifying the facial phenotype, including prominent forehead, midface retraction, and short, upturned nose, plus one of either of the two other major distinguishing features: typical skeletal abnormalities or hydronephrosis. Typical skeletal anomalies include a sclerotic skull base, wide supraoccipital-exoccipital synchondrosis, increased cortical density or thickness, and broad ribs. Other highly supportive features include neuroepithelial tumors (found in 17%), hypertrichosis, and brain abnormalities. Severe developmental delay and poor survival are constant features in reported patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".