Bibliographic record
Abstract
What Is the Issue? There is a need to identify drugs currently in development (pipeline drugs) intended to prevent or treat influenza. Specifically, policy-makers would like to identify those drugs that have ongoing or recently completed phase II or phase III randomized controlled trials (RCTs) and are not yet approved for use by Health Canada for influenza. What Did We Do? An information specialist did a tailored literature search across major databases to identify relevant RCTs on antiviral drugs for influenza, focusing on information published in English since January 1, 2020, and completed on November 8, 2024. What Did We Find? We identified a total of 17 emerging drugs in 26 completed or ongoing RCTs, mainly testing treatments for adults with uncomplicated influenza, with some studies including children and adolescents. The evidence included 2 prevention studies and 3 challenge studies for influenza. Most drugs were compared to a placebo and the number of participants in these trials ranged from 46 to 5,000. What Does It Mean? There are promising new drugs in development for treating adults with uncomplicated influenza.
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 | 0.014 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 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".