Bibliographic record
Abstract
With the judicious use of inhaled corticosteroids, beta2 agonists, and leukotriene modifiers, most patients with asthma are easily controlled and managed. However, approximately 5% of asthmatics do not respond to standard therapy and are classified as "difficult to control." 1 Typically, these are patients who complain of symptoms interfering with daily living despite long-term treatment with inhaled corticosteroids in doses up to 2,000 mug daily. Many factors can contribute to poor response to conventional therapy, and especially for these patients, a systematic approach is needed to identify the underlying causes. First, the diagnosis of asthma and adherence to the medication regimen should be confirmed. Next, potential persisting exacerbating triggers need to be identified and addressed. Concomitant disorders should be discovered and treated. Lastly, the impact and implications of socioeconomic and psychological factors on disease control can be significant and should be acknowledged and discussed with the individual patient. Less conventional and novel strategies for treating corticosteroid-resistant asthma do exist. However, their use is based on small studies that do not meet evidence-based criteria; therefore, it is essential to sort through and address the above issues before reverting to other therapy.
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 | 0.033 | 0.078 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.016 | 0.006 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".