Bosma Arhinia Microphthalmia Syndrome (BAMS): First Report from Vietnam
Bibliographic record
Abstract
Bosma arhinia microphthalmia syndrome (BAMS) is a rare condition, with about 100 cases identified worldwide. It is characterized by nasal and ophthalmic abnormalities, as well as disturbances in puberty and sexual development. The cardinal sign is arhinia, though some cases have partial aplasia of the external nose. In addition, several reports have revealed abnormal brain structure, including changes to the olfactory bulbs. This case describes a 29-year-old female who has suffered from BAMS since birth. On presentation, she was noted to have congenital arhinia, bilateral microphthalmia, vision loss, mouth-breathing, an unclear speaking voice, a high arched or cleft palate, and a hypoplastic maxilla. Her paranasal sinuses were ossified and underdeveloped. This syndrome occurs rarely, both within Vietnam and worldwide. It is characterized by four major features: arrhinia, complete absence of the paranasal sinuses, eye defects, and absent sexual maturation. This case report describes the presentation of the disorder to improve otolaryngologists' understanding of BAMS. Criteria for diagnosis consist of arhinia, midface hypoplasia (with a hypoplastic maxilla), hypogonadotropic hypogonadism, and normal intellectual abilities. Additional important findings are microphthalmia with or without coloboma, anosmia, maxillary hypoplasia, a high-arched palate, and absence of paranasal sinuses and olfactory bulbs.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".