Quantitative High-Speed Video Profiling Discriminates between <i>DNAH11</i> and <i>HYDIN</i> Variants of Primary Ciliary Dyskinesia
Bibliographic record
Abstract
Primary ciliary dyskinesia (PCD) is a genetically heterogeneous condition. The number of genes associated with primary ciliary dyskinesia is rising, and the link between genotype and clinical phenotype is largely unknown (1). Recent advances in molecular genotyping have helped establish the association between genetic defects and aberrant cilia ultrastructure in PCD, as detected by transmission electron microscopy. However, up to 30% of PCD cases do not show any specific ultrastructural defects and thus cannot be detected using this method. A classic example of this occurs in PCD cases caused by mutations in the DNAH11 (dynein axonemal heavy chain 1) protein, where aberrant ciliary beating can be detected via high-speed video microscopy (HSVM) analysis, but no ultrastructural defect is observed (2, 3). Even in cases where ultrastructural defects do exist, they can be difficult to detect using standard transmission electron microscopy techniques, and therefore patients who harbor such subtle defects are at risk of being misdiagnosed. PCD caused by mutations in the protein HYDIN, for example, display normal ciliary beat frequency and rarely exhibit abnormal ciliary transmission electron microscopy, yet mucociliary clearance is compromised.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".