Bibliographic record
Abstract
In this issue of the Canadian Respiratory Journal, Cowie et al (pages 555‐558) make the startling claim that "inhaled corticosteroid therapy does not control asthma". This sounds crazy: if inhaled steroids don′t control asthma, what does? It turns out not to be crazy. Cowie et al reported on the effectiveness of asthma control according to Canadian guidelines (1) in several large groups of asthmatics evaluated by cross‐sectional, one‐point‐in‐time questionnaires. They found that patients on inhaled steroids were less well‐controlled than those who were not on inhaled steroids, and that there was a dose effect, in that the larger the dose of inhaled steroids the worse the control. There is, of course, a simple explanation for this; patients with hard‐to‐control asthma are likely to be prescribed inhaled steroids, and the harder the disease is to control, the higher the dose. However, these findings are compatible with inhaled steroids having a minor effect on asthma control, something that we do not believe (2). There are excellent data from clinical trials (3) that inhaled steroids work, and in population studies (4), their use is associated with improved survival.
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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.015 | 0.012 |
| Insufficient payload (model declined to judge) | 0.011 | 0.007 |
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".