Bibliographic record
Abstract
Chronic cough is defined as a cough persisting for longer than 8 weeks. Chronic cough is common, with an approximate prevalence of 10% of the global population. In Canada, recent estimates indicate that the prevalence of cough is 16% among adults aged 45-85 years. Chronic cough can interrupt work, sleep, and social interactions, making it very troubling for patients, with impacts on physical, social, and psychological health. Cough is one of the leading causes of visits to primary care practitioners. The peak incidence for presentation to primary care is among individuals in the 50-60 years age group and it is twice as frequent in women. Currently, most clinicians address cough as a symptom of other medical conditions, which leads to trials of treatments for diseases that may not be present. This approach can lead to unnecessary costs, frustration for both clinicians and patients, and potential harms from the therapies prescribed. Instead, a diagnostic work up needs to be performed to identify refractory chronic cough as a distinct disease entity, resulting from afferent neuronal hypersensitivity and central nervous system dysfunction. The secondary factors that aggravate chronic cough (smoking, asthma, gastro-esophageal reflux, among others) should be considered as treatable traits associated with the primary disease process rather than only the direct causes of the cough.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".