Revisiting <scp>T</scp>ype 2‐high and <scp>T</scp>ype 2‐low airway inflammation in asthma: current knowledge and therapeutic implications
Bibliographic record
Abstract
Asthma is a complex respiratory disorder characterized by marked heterogeneity in individual patient disease triggers and response to therapy. Several asthma phenotypes have now been identified, each defined by a unique interaction between genetic and environmental factors, including inflammatory, clinical and trigger-related phenotypes. Endotypes further describe the functional or pathophysiologic mechanisms underlying the patient's disease. type 2-driven asthma is an emerging nomenclature for a common subtype of asthma and is characterized by the release of signature cytokines IL-4, IL-5 and IL-13 from cells of both the innate and adaptive immune systems. A number of well-recognized biomarkers have been linked to mechanisms involved in type 2 airway inflammation, including fractional exhaled nitric oxide, serum IgE, periostin, and blood and sputum eosinophils. These type 2 cytokines are targets for pharmaceutical intervention, and a number of therapeutic options are under clinical investigation for the management of patients with uncontrolled severe asthma. Anticipating and understanding the heterogeneity of asthma and subsequent improved characterization of different phenotypes and endotypes must guide the selection of treatment to meet individual patients' needs.
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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) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".