Bibliographic record
Abstract
Cystic fibrosis (CF) is caused by mutations in the cystic fibrosis transmembrane regulator (CFTR) gene, and more than 1,500 distinct mutations with different functional consequences have been reported in the CFTR database (1). Multiple organs are involved in the disease process, but lung disease continues to account for the majority of morbidity and mortality in patients with CF. Knowledge about the pathophysiology of cystic fibrosis has greatly increased in recent years and CF has evolved into a model demonstrating how a better understanding of the underlying defect can lead to novel therapeutic approaches. However, complex interactions exist between CFTR and other regulatory proteins and all of the relevant components that cause disease manifestations both in the lung and in other organ systems are still incompletely understood. A large body of evidence supports the concept that airway surface liquid depletion is a key component in the development of CF lung disease. This is thought to be the consequence of an imbalance in defective chloride secretion and enhanced sodium absorption that has been consistently observed in studies of CF epithelium. The net fluid loss on the airway surface leads to the collapse of cilia and impaired mucociliary transport. However, regulation of mucociliary clearance is a dynamic process involving other epithelial channels that are thought to play an important role in stress-induced increases in airway surface liquid (ASL) height (2). These CFTR independent pathways are functional in CF and can be up-regulated by both external and internal stimuli, such as ATP, which may explain why mucociliary clearance is reduced but not absent in patients with CF (2). Improving airway surface hydration either with pharmacological agents or osmotic agents, such as hypertonic saline, has become an important therapeutic target in CF (3, 4).
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.102 | 0.056 |
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".