Provoked models of asthma: what have we learnt?
Bibliographic record
Abstract
Asthma is a chronic inflammatory disease of the airways characterized by physiological abnormalities of variable airflow obstruction and airway hyperresponsiveness (AHR) to a wide variety of physical and inhaled chemical stimuli and the presence of symptoms. AHR is measured by challenging the airways with a variety of agonists and naturally occurring stimuli, which results in constriction of the airway smooth muscle, leading to airway narrowing and airflow limitation. There are two distinct mechanisms by which the airways can narrow to a constrictor stimulus and these are defined by the pathways they take to induce AHR. Direct stimuli are pharmacological agents administered exogenously (such as histamine or methacholine) that act 'directly' on specific receptors on the bronchial smooth muscle to cause constriction. The other mechanism by which the airway can narrow is via the inhalation of indirect stimuli, which include natural stimuli, such as allergen or exercise, and pharmacological agents such as adenosine monophosphate and hyper-osmotic agents (e.g. hypertonic saline or dry powder mannitol). These stimuli induce airway narrowing 'indirectly' by causing the endogenous release of mediators of bronchoconstriction from airway inflammatory cells. Provoked models of asthma have been extremely valuable in understanding the pathobiology of asthma, in aiding diagnosis, in helping to clarify the mechanisms of actions of effective drugs and in the development of new entities to treat asthma. Some provoked models are valuable clinically, particularly those that measure direct AHR, while others, particularly allergen challenge, have been used in animal models and in humans to study the mechanisms of allergen-induced airway inflammation and the associated physiological changes, as well in the development of new drugs for asthma. An emerging role for measurements of AHR is in the evaluation of the optimal treatment for patients with asthma.
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.005 | 0.009 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.006 | 0.014 |
| Insufficient payload (model declined to judge) | 0.007 | 0.004 |
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".