Primary ciliary dyskinesia: mechanisms and management
Bibliographic record
Abstract
Nadirah Damseh,1 Nada Quercia,1,2 Nisreen Rumman,3 Sharon D Dell,4 Raymond H Kim5 1Division of Clinical and Metabolic Genetics, 2Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada; 3Pediatric Department, Makassed Hospital, Jerusalem, Palestine; 4Division of Respiratory Medicine, Department of Pediatrics, Child Health Evaluative Sciences, Hospital for Sick Children, 5Fred A Litwin Family Centre in Genetic Medicine, University Health Network and Mount Sinai Hospital, Department of Medicine, University of Toronto, Toronto, ON, Canada Abstract: Primary ciliary dyskinesia is a genetically heterogeneous disorder of motile cilia that is predominantly inherited in an autosomal-recessive fashion. It is associated with abnormal ciliary structure and/or function leading to chronic upper and lower respiratory tract infections, male infertility, and situs inversus. The estimated prevalence of primary ciliary dyskinesia is approximately one in 10,000–40,000 live births. Diagnosis depends on clinical presentation, nasal nitric oxide, high-speed video-microscopy analysis, transmission electron microscopy, genetic testing, and immunofluorescence. Here, we review its clinical features, diagnostic methods, molecular basis, and available therapies. Keywords: genetic testing, Kartagener’s syndrome, primary ciliary dyskinesia
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".