Modifier Gene Studies to Identify New Therapeutic Targets in Cystic Fibrosis
Bibliographic record
Abstract
Since the discovery of the CFTR gene mutations which cause cystic fibrosis (CF) in 1989 the average life expectancy of CF patients has almost doubled and now exceeds 37 years. The advances in molecular diagnostics and medical treatments expanded beyond the CF patient population as some of the newest treatments are also being tested for treatment of complex diseases such as COPD and other inherited disorders. Rapid development of CF therapeutics is important for the cystic fibrosis community and is an excellent example for other nonprofit organizations, disease foundations and pharmaceutical companies alike. Better understanding of disease variability and underlying molecular mechanisms through genetic association studies aimed to identify novel CF modifier genes opens new venues for targeted drug design. Furthermore, these genetic studies allow development of molecular diagnostic tests for patient population stratification and treatment personalization, which is already being done for CF patients with specific mutations in the CFTR gene, as well as implementation of new molecular tests for reliable assessment of disease progression and severity.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".