Bibliographic record
Abstract
In this Update we will discuss aspects of the definitions, epidemiology, diagnostics, asthma-associated comorbidities, assessment and treatment of asthma including a specific focus on severe asthma in school children. The Update will mainly cover data published during the last 3 yrs. In 2009, an expert panel was tasked to propose a World Health Organization definition of asthma severity and control. The result of this Task Force was a uniform definition of asthma severity, control and exacerbation [1]. As we will discuss later in an overview of asthma outcomes [2], symptom evaluation is the key to the diagnosis and outcome measures in clinical studies. Airway inflammation is one of the pathophysiological characteristics of asthma, which is mediated through infiltration of inflammatory cells, including mast cells, and eosinophilic and neutrophilic granulocytes in the airway wall. This cell infiltration subsequently leads to bronchial hyperresponsiveness (BHR) and, in the case of chronic inflammation, persistent changes of the airways, i.e. airway remodelling [3, 4]. Immunoglobulin (Ig)E-mediated allergy leading to allergic inflammation is common among children with persistent asthma. There are ongoing studies worldwide (the MeDALL initiative) aiming to identify allergic phenotypes [5] and understand the complexity of the IgE related phenotypes in children and adults [6]. The purpose of paediatric asthma treatment is for the child to control symptoms, to be able to lead a normal active life, to have normal lung function and to prevent asthma exacerbations [7, 8]. The care of asthmatic children does not only include the prescription of asthma medication. The families need to be convinced and educated to actually make the parents give the medication as prescribed and in a proper manner [9]. Furthermore, healthcare providers must teach the families how to avoid or …
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.054 | 0.030 |
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".