Cornelia de Lange syndrome in diverse populations
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Cornelia de Lange syndrome (CdLS) is a dominant multisystemic malformation syndrome due to mutations in five genes-NIPBL, SMC1A, HDAC8, SMC3, and RAD21. The characteristic facial dysmorphisms include microcephaly, arched eyebrows, synophrys, short nose with depressed bridge and anteverted nares, long philtrum, thin lips, micrognathia, and hypertrichosis. Most affected individuals have intellectual disability, growth deficiency, and upper limb anomalies. This study looked at individuals from diverse populations with both clinical and molecularly confirmed diagnoses of CdLS by facial analysis technology. Clinical data and images from 246 individuals with CdLS were obtained from 15 countries. This cohort included 49% female patients and ages ranged from infancy to 37 years. Individuals were grouped into ancestry categories of African descent, Asian, Latin American, Middle Eastern, and Caucasian. Across these populations, 14 features showed a statistically significant difference. The most common facial features found in all ancestry groups included synophrys, short nose with anteverted nares, and a long philtrum with thin vermillion of the upper lip. Using facial analysis technology we compared 246 individuals with CdLS to 246 gender/age matched controls and found that sensitivity was equal or greater than 95% for all groups. Specificity was equal or greater than 91%. In conclusion, we present consistent clinical findings from global populations with CdLS while demonstrating how facial analysis technology can be a tool to support accurate diagnoses in the clinical setting. This work, along with prior studies in this arena, will assist in earlier detection, recognition, and treatment of CdLS worldwide.
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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 | 0.000 |
| 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 | 0.000 |
| 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 it