Monitoring the Impact of Asthma Drug Therapy: Database Studies
Bibliographic record
Abstract
To bring a drug to market regulatory agencies require demonstration ofbenefit on a narrow range of outcomes and a lack of safety concerns. For asthma, the outcome of many randomized clinical trials has been a measureof flow such as FEV1 or PEF, as well as symptoms and use of rescue med-ications. More recently, measures of quality of life have been added tobroaden the scope of benefits examined. These randomized clinical trialsoften do not have sufficient power or duration of follow-up to allow oneto compare the rates of clinically important outcomes such as severeexacerbations requiring hospitalization, death, or long-term non-respira-tory effects, for example, on growth or bone metabolism. Moreover, the selection criteria for clinical trials are quite strict. Subjects are usuallyrequired to be non-smokers, to have little or no co-morbid disease, andSamy Suissa is the recipient of a Distinguished Scientist award from the Canadian Institutes of Health Research.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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 teacher head, 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".