Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Animal models have been developed to investigate specific components of asthmatic airway inflammation, hyper-responsiveness or remodelling. However, all of these aspects are rarely observed in the same animal. Heaves is a naturally occurring disease of horses that combines these features. It is characterized by stable dust-induced inflammation, bronchospasm and remodelling. The evaluation of horses during well-controlled natural antigen exposure and avoidance in experimental settings allows the study of disease mechanisms in the asymptomatic and symptomatic stages, an approach rarely feasible in humans. Also, the disease can be followed over several years to observe the cumulative effect of repeated episodes of clinical exacerbation or to evaluate long-term treatment, contrasting most murine asthma models. This model has shown complex gene and environment interactions, the involvement of both innate and adaptive responses to inflammation, and the contribution of bronchospasm and tissue remodelling to airway obstruction, all occurring in a natural setting. Similarities with the human asthmatic airways are well described and the model is currently being used to evaluate airway remodelling and its reversibility in ways that are not possible in people for ethical reasons. Tools including antibodies, recombinant proteins or gene arrays, as well as methods for sampling tissues and assessing lung function in the horse are constantly evolving to facilitate the study of this animal model. Research perspectives that can be relevant to asthma include the role of neutrophils in airway inflammation and their response to corticosteroids, systemic response to pulmonary inflammation, and maintaining athletic capacities with early intervention.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 it