Primary Ciliary Dyskinesia
Bibliographic record
Abstract
Primary ciliary dyskinesia (PCD) is a rare but underdiagnosed disorder that affects motile cilia function throughout the body. With increasing prevalence through ongoing genetic discovery, PCD underlies the disease process in a significant number of patients with chronic suppurative lung disease and bronchiectasis when properly investigated using current diagnostic standards. Classic PCD symptoms include chronic rhinosinusitis and otitis, organ laterality defects, infertility, year-round productive cough, and recurrent pneumonias with bronchiectasis. Clinical symptoms of PCD manifest very early in life (often at birth), although diagnosis frequently is delayed because of poor phenotypic recognition and limited access to specialized diagnostic testing. In the past decade, PCD research networks have established specific PCD phenotypes to increase clinical recognition, and the availability of PCD genetic panels in various commercial laboratories has expanded access to an accurate PCD diagnosis greatly. Clinical practice guidelines also were created to guide diagnosis and management of this rare but increasingly recognized suppurative respiratory disease. PCD is more common than previously thought and can be recognized through specific clinical phenotypes in both children and adults. Diagnostic PCD testing outside of highly specialized centers can be difficult, but increased availability of nasal nitric oxide measurement and commercial genetic panels now allows for noninvasive screening and definitive diagnosis regardless of center expertise. Identification of patients with accurately diagnosed PCD is needed worldwide to populate future clinical trials and to develop disease-specific therapies for PCD.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.005 |
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".