Characterizing the oculoauriculofrontonasal syndrome
Bibliographic record
Abstract
Human dysmorphology syndromes are frequently defined by characteristic abnormalities in facial morphogenesis. Two such well recognized syndromes are the oculoauriculovertebral spectrum (OAVS) and frontonasal dysplasia (FND). OAVS is diagnosed on the basis of the presence of typical facial features which can include microtia, preauricular tags, hemifacial microsomia, lateral face clefting, epibulbar dermoids, and upper palpebral colobomata. FND is characterized by ocular hypertelorism, nasal clefting, and anterior cranium bifidum occultum. After the first patient was described with features of both OAVS and FND, at least a further 25 patients presenting the 'oculoauriculofrontonasal syndrome' (OAFNS) have been reported. We report on four more patients with OAFNS and review their features, together with those of the other patients reported in the medical literature. We suggest that, statistically, OAFNS is more likely to be a sporadically occurring condition rather than an inherited autosomal recessive trait, as previously suggested. We cannot, however, definitively exclude the possibility of autosomal dominant transmission. Considering the question of whether OAFNS is a part of OAVS, FND, or a distinct clinical entity, we conclude that, for the time being, OAFNS should be considered to be a distinct syndrome, to further our understanding of the aetiology of these conditions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".